menett22 vol 1 (aec drc)

22 15-17 2551

ME NETT 22ME NETT 22ME NETT 22ME NETT 22ME NETT 22

1

Alternate Energy and Combustion

Dynamic Systems, Robotics and Control

1 22 1

15-17 2551

ME NETT 22ME NETT 22ME NETT 22ME NETT 22ME NETT 22

1

Alternate Energy and Combustion

Dynamic Systems, Robotics and Control

1 22 2

1 22

ISBN 978 - 974 - 466 -340 - 5

: . . 12120

: .. 2551

1 22 3

22

22 (ME NETT 22) 15-17 2551

267 Alternative Energy andCombustion (AEC) 35 Aerospace and Marine Engineering (AME) 6 AppliedMechanics, Material and Manufacturing (AMM) 64 Biomechanics (BME) 7 Computationand Simulation Techniques (CST) 32 Dynamic Systems, Robotics and Control (DRC) 34 Energy Technology and Management (ETM) 36 Thermal Systems and FluidMechanics (TSF) 49 234

4 1

Alternative Energy and Combustion (AEC)Dynamic Systems, Robotics and Control (DRC)

2Aerospace and Marine Engineering (AME)Applied Mechanics, Material and Manufacturing (AMM)

3Biomechanics (BME)Energy Technology and Management (ETM)

4Computation and Simulation Techniques (CST)Thermal Systems and Fluid Mechanics (TSF)

1 22 4

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1. Alternative Energy and Combustion (AEC)

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2. Dynamic Systems, Robotics and Control(DRC)

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.. . Asst. Prof. Dr. Metthew Owen Thomas Cole. . . .

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........................................................................................................................................ 3 22 ..... 4 ........................................................................................ 5 ............................................................................................................ 8 ................................................................................................................ 429

1 22 8

1. Alternative Energy and Combustion (AEC)AEC001 Weibull Rayleigh

( , ) ................................... 3(Wind Power Potential Analysis Based on the Weibull and Rayleigh Distribution(Case Study at Monlan Royal Project, Chiang Mai))

AEC002 ................................... 8(A Study of Using Emulsion of Heavy Oil and Water in a Thermal Oil Boiler)

AEC003 A Submicron Electrical Aerosol Detection System with a Faraday Cup Electrometer ............. 14AEC004 ............................................................ 20

(Performance Evaluation of Incinerator for Community-Based Solid Waste Management)AEC005

........................................................................................... 26(Optimal Placement of Biogas Plant from Cow Dung by Geographic Information System)

AEC006 DME .................. 31(Analysis of Energy Release of CI Engine Operating on DME)

AEC007 ............................................... 36(Feasibility Study of Biomass Quality for Wood Pellets)

AEC008 : ............................................................................................................ 41(Experiment Test of Biodiesel in Single Cylinder Diesel Engine: Performance, Black Smokeand Long Term Evaluation)

AEC009 - .......... 46(Experimental Study of Performance in Carburetor System Motorcycle withJatropha-Gasoline Blended Fuel)

AEC010 .................................................................................................................... 53(Feasibility Study of Anhydrous Ethanol Blended with Gasoline for Small Aircraft Engine)

AEC011 ................................... 59(Electrostatic precipitator for collection of particles from rubber wood combustion)

AEC012 EGR . 64(Effects of EGR on Diesel Engine-Operating Characteristicsunder Different Engine Conditions)

AEC013 Characterization of Insoluble Impurities in Biodiesel from Palm Stearin ................................... 70AEC014

.............................................................................................. 74(Analysis of Metered water Injection into High-Temperature Mixture ofCombustion Products in a Cylinder of Spark Ignition Engine)

1 22 9

AEC015 ................................................................................... 81(Manufacturing of a Alpha Type Stirling Engine)

AEC016 .......... 86(An Analysis Small Engine Using Biogas From Elephant Dung for the Generator)

AEC017 ....................................................................................................... 92(Effect of Ignition Timing on Performance and Exhaust Gas Temperature ofa Diesel Engine Converted for use with Natural Gas Fuel)

AEC018 IDI ................................................................................................. 99(Performance and Emission Characteristics of Using Degummed,Deacidified Palm Oil-Diesel Blends in Vehicle Diesel Engine (IDI))

AEC019 .............. 106(A Study of Palm Bio-Diesel Stoichiometric Air to Fuel Ratio)

AEC020 .................................................................................................................. 111(A Study of Injection Advance Timing in Diesel Commonrail EngineUsing Bio-diesel as Alternative Fuel)

AEC021 .............................................................. 116(Development of Low-Cost Dynamometer using Hydrostatic System)

AEC022 20 .......................... 121(The investigation of E20 impacts on fuel supply parts of Motorcyclein Thailand Material compatibility tests)

AEC023 20 ....................................... 128(The investigation of E20 impacts on fuel supply parts of passenger vehiclesin Thailand Material compatibility tests)

AEC024 ......................... 134(Computer Controlled Dynamometer for Small Engine)

AEC025 ...... 137(The of Effect of The Angle of Orientation on Flame Spread Over Combustible Sheet)

AEC026 ................................. 142(Temperature Effect on Octane Number of Hydrocabon Mixtures for Gasoline Fuel)

AEC027 ... 148(The investigation of performance of engined power generator by usingbiomass gases and biodiesel)

AEC028 ......................... 154(Nonpremixed Porous Burners for Gaseous Fuels)

1 22 10

AEC029 ............................................................................................................ 160(Visualization of tangential flow inside the cylinder tube usingParticle Image Velocimetry (PIV))

AEC030 .................................................................................................. 168(Ethanol Fuel Motorcycle)

AEC031 ............................................. 174(Injection and Ignition Control System for Racing Engine)

AEC032 ............................................................................... 180(The Effect of Natural Gas Compositions Variation from East and North Sourceson Engine Characteristics)

AEC033 .................................... 187(Numerical investigation of premixed combustion in porous media)

AEC034 ................................................................................................. 194(Effects of an incomplete transesterification process in producing palm oil biodieselon an engine performance)

AEC035 . 200(A Simple Measurement Technique of Compressed Natural Gas Consumptionfor Engine Testing)

AEC036 .............................. 204Axial Momentum Theory for Contra Rotating Rotors Wind Turbine

2. Dynamic Systems, Robotics and Control (DRC)DRC001

............................................................................................. 213(Estimation of DC Motor Variable Torque Using Adaptive Compensation)

DRC002 ..................... 220(PID Controller Design and Analysis for Infrared Oven)

DRC003 ..................................................................................... 227(A Study of Engine Vibration)

DRC004 .............................. 234(Condition monitoring of compressor using Principal component analysis (PCA) method)

DRC005 ................................................. 242(Transmission Error Compensation for Heliostats)

DRC006 .......................................... 248(Road characteristic model for golf cart design)

1 22 11

DRC007 .................... 254(The Comparison of Using Maximum Energy and Maximum Jerk With given both endof Control Input in Dynamic System Application in High Speed Elevator)

DRC008 3 ..................................................................................................... 258(Control of 3D Inverted Pendulum)

DRC009 .............................. 264(The Design of Control Engineering Laboratory Using Virtual Instrumentations)

DRC010 ................................................................................... 269(Equivalent Dynamic Scaling System for Real Vehicle)

DRC011 ........................ 275(Dynamic states calculation based on 2 and 3 Dimensional vehicle models)

DRC012 Design and development of a mechanical device for treatment of venous congestion ......... 281DRC013 ...................................... 287

(Optimal Path Planning Algorithm for Humanoid Robot)DRC014 6 ......................................................... 293

(A 6-DOF Master Slave System for Miniature Tasks)DRC015 Development of A 3-D Solid Modeling System Based on The Parasolid Kernel

for Gem Stones Faceting ......................................................................................................... 300DRC016 Embedded Force Control for a Hybrid 5-Axis H-4 Family Parallel Manipulator ........................ 308DRC017 PA10-7C.................................................. 314

(Kinematics ans Dynamics Analysis of the PA10-7C Manipulator Arm.)DRC018 Analytical Kinematics and Dynamics for A 5-axis H-4 parallel Manipulator .............................. 322DRC019 H-4 5 ......... 334

(NC Code Interpreter for A 5-Axis H-4 Family Parallel Manipulator with A Rolling Table)DRC020 ............................................ 339

(Impedance Control of Robot for Human-Robot Cooperative Task)DRC021 ............................................................... 346

(Active Noise Control Using Frequency Splitting Techniques)DRC022 ................................................................................. 352

(Design and Analysis of an adjustable Wheel-legs for Stair Climbing Robot)DRC023 ................. 358

(Tire-Suspension-Steering Hardware-In-The-Loop for Vehicle Dynamic Simulation)DRC024 .......................................................... 365

(Robot Programming by Demonstrations for Assembly Task)DRC025

.......................................................................... 370(Study and improve the quality of Sugar cane loader in Thai agriculturebased on vibration Engineering)

1 22 12

DRC026 ....................... 376(Optimal Control of a Two-wheeled Robot with High Bandwidth Tilt Measurement)

DRC027 Vibration Monitoring System for Optimum Operation of Hydraulic Turbineof Nam Ngum1 Hydro Power Plant ......................................................................................... 382

DRC028 ....................... 387(Application of the Edge Detection in Plastic-Sheet Puncher Control Program)

DRC029 .......................................................... 393(Quantitative Feedback Control of a Two-Link Robot Manipulator)

DRC030 ................................................ 399(Exact Mathematical Modeling of a One-link Flexible-link Robot Manipulator)

DRC031 ..................... 405(Effect of stator stiffness for generating traveling wave on an ultrasonic curvilinear motor)

DRC032 PID ............................... 409(Simulation of optimal PID controller of piezoelectric actuator)

DRC033 ................................................................. 414(Quantitative Feedback Control of Hard Disk Actuator)

DRC034 ................................................................................................... 420(Vibration Study and Analysis of Vertical Cartesian Robot using The Finite Element Method)

DRC035 ............................................ 424Development temperature control in microwave oven by fuzzy logic method

Alternative Energy and Combustion (AEC)

AEC001

1 22 3

Weibull Rayleigh ( , )

Wind Power Potential Analysis Based on the Weibull and Rayleigh Distribution (Case Study at Monlan Royal Project, Chiang Mai)

1, 2 3 1 .

* 0815406768, E-mail:[email protected] 2 .

053942005, E-mail:[email protected] 3 .

053-875140 E-mail:[email protected]

Weibull Rayleigh 20, 30 40 40 10 4.86 / 2.11 / 75.04 / 40 Weibull Rayleigh

Abstract The wind power potential at Monlan Royal Project, Chiang Mai Province, THAILAND was studied based on the Weibull and Rayleigh distribution model. The wind speed data and wind direction was averaged and recorded every 10 minutes. The wind speed was measured at a height of 20, 30 and 40 m above ground level by cup type anemometer. The wind direction was measured by wind vane at a height of 40 m above ground level. It was found that wind was from N.W. to S.E. direction. The yearly average of wind speed was 4.86 m/s with the standard deviation values of 2.11 m/s. Wind speed at night was high than wind speed at day. The yearly average of wind power value was 75.04 W/m2 at a height of 40 m above ground level. The Weibull distribution provided better power density estimations than the Rayleigh distribution.

1. (Introduction) 50 Solar home system ( 4.0-7.0 /) 2 .

4 1 22

1 [1]

Weibull Rayleigh 2

2. (Data) 40 19o25.821/ N; 99o18.310/E 1,573

20 M

30 M

40 M

Anemometer

Anemometer

Anemometer

Wind Vane

DATA LOGGER

2

3 20, 30 40 40 10 2550 2551

3. (Average wind speed, standard deviation and wind direction)

Wind speed frequency distribution histogram 1 2 [2] 1 40 4.86 / 2.11 / 0.6 / 3

=

= BN

iiinmN

V1

1 (1)

= =

BN

iiiV VNnmN 1

22 )(1

1 (2)

V , (m/s) V , (m/s) im i (m/s) in i (h) N (h) BN

1 40 V (m/s) V (m/s) k c (m/s)

..-50 ..-50 ..-50 ..-50 ..-50 ..-50 ..-51 ..-51

6.35 4.94 4.09 4.41 5.24 4.23 4.36 5.27 4.95 4.70

1.95 2.66 1.94 2.34 2.07 1.85 2.19 1.91 2.22 2.04

3.69 1.74 1.84 1.77 2.82 2.82 2.08 3.16 2.26 2.58

6.52 4.97 3.75 3.70 4.58 4.58 4.53 5.42 4.74 4.82

Analyzed from 243 daysHeight of Cup Animometer (above ground level)

0.0

1.0

2.0

3.0

4.0

5.0

6.0

0 2 4 6 8 10 12 14 16 18 20 22

hour of day (0 is a midnight)

Win

d Sp

eed

(m/s

)

20 m 30 m 40 m

3

4

1 22 5

4

4. Wind Shear Coefficients 0

2 [3] (Wind Shear Coefficient) 3 5 Wind Shear Coefficient Wind Shear Coefficient

=

rrZ Z

ZVV )( (3)

Z (m) rZ (m) rV (m/s) rZ zV (m/s) Z Wind Shear Coefficient

5

5. (Wind speed distribution analysis)

3 , )(Vf Weibull ( 4) Rayleigh ( 5) 2550 40 2 6 3 - 7 /

= kk

W cV

cV

ckVf exp)(

1

(4)

=2

22 4exp

2)(

VV

VVVf R

(5) C (Scale Parameter k (Shape Parameter)

2 , Weibull Rayleigh ( 2550) 40

Rang (m/s) im (m/s) )(Vf WVf )( RVf )( 0-1 0.5 0.1 0.1 1.9 1-2 1.5 0.8 1.1 5.6 2-3 2.5 3.8 4.2 8.6 3-4 3.5 7.6 9.6 10.7 4-5 4.5 12.1 16.2 11.8 5-6 5.5 18.5 21.0 11.9 6-7 6.5 18.5 20.9 11.1 7-8 7.5 17.0 15.4 9.8 8-9 8.5 13.1 8.1 8.1 9-10 9.5 6.3 2.8 6.4 10-11 10.5 2.1 0.6 4.8 11-12 11.5 0.0 0.1 3.4 12-13 12.5 0.0 0.0 2.3

0

5

10

15

20

25

0 2 4 6 8 10 12 14 16

W ind Speed (m /s )

Prop

abilit

y Den

sity (

%)

. .-50. .-50 ..-50 . .-50..-50 . .-50 . .-51 ..-51

6

(Pow er Exponent)

0

20

40

60

80

100

120

140

160

0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00

Wind Speed (m/s)

Hig

ht a

bove

gro

und

leve

l (m

)

.. -50 (0.109)

..-50 (0.140)

..-50 (0.284)

..-50 (0.416)

..-50 (0.354)

..-50 (0.138)

..-51 (0.107)

..-51 (0.101)

Hei

ght (

m)

6 1 22

6. (Power density distribution analysis) 6

321)( VVP = (6)

Weibull Rayleigh 7 8 [4]

+=k

cVP W31

21)( 3 (7)

33)( VVP R = (8) )(x Gamma function =

0

1)( dttex xt . (9)

Gamma function [5]

( )( )( ) +++= ...51840139288112112)( 321 xxxexxx xx (10) 6, 7 8 7

0

50

100

150

200

250

..-50 ..-50 ..-50 ..-50 ..-50 ..-50 ..-51 ..-51

month

Pow

er d

ensi

ty (W

/sq-

m)

Weibull

Rayleigh

7

6 7 8 Weibull Rayleigh Weibull Rayleigh 8 Weibull Rayleigh 11

)(

)()((%) ),(

VPVPVP

Error RWModel= (11)

-40

-20

0

20

40

60

80

..-50 ..-50 ..-50 ..-50 ..-50 ..-50 ..-51 ..-51

Month

Erro

r (%

)

Weibull

Rayleigh

8

7. (Conclusion) 1. 4.86 /

2.11 /

2. Wind Shear Coefficient

3.

4. 75.04 /

5. Weibull Rayleigh

8. (Acknowledgement) PARA and FAME Laboratory . .

9. (Bibliography) [1] Google Earth Program, , 25 2551 [2] J. F. Manwell., J. G. McGowan. and A. L. Rogers. 2002. Wind

Energy Explained. John Wiley & Sons, Baffins Lane, Chic Hester, West Sussex PO19 1UD, England

[3] John F. Walker. and Nicholas Jenkins. 1997. Wind Energy Technology. John Wiley & Sons. Baffins Lane, Chic Hester, West Sussex PO19 1UD, England

[4] Ali Naci Celik. 2003. Statistical analysis of wind power density Based on the Weibull and Rayleigh models at the southern region of Turkey. Renewable Energy V29. 593-604.

1 22 7

[5] Jamil, M. 1994. Wind Power Statistic and Evaluation of Wind Energy Density, Wind Engineering, 18, No.5, 227-240.

AEC002

8 1 22

A Study of Using Emulsion of Heavy Oil and Water in a Thermal Oil Boiler

*

126 10140 [email protected]

580 kW (W=0%) 11.8%, 18.0% 22.0% (W/O, 11.8%; W/O, 18.0%; W/O, 22.0%) 11.8% 81.04% 85.49% 5.20% 9.16% NOx SO2 Abstract Since heavy oil is low quality fuel, it is difficult to get complete combustion. This research aims to study the use of heavy oil mixed with water in the form of emulsion in order to improve combustion efficiency and to find out an appropriate ratio between heavy oil and water in emulsion. The experiments were conducted in a combustion chamber of thermal oil boiler with 580 kW capacity. Fuels used in this study are heavy oil (W=0%) and water-in-oil emulsion, 11.8%, 18.0% and 22.0% (W/O, 11.8%; W/O, 18.0%; W/O, 22.0%) by volume, respectively. The results show that the appropriate ratio between water and heavy oil is at 11.8% by volume. At this ratio, the thermal efficiency of hot oil boiler increases from 81.04% to 85.49%. Fuel saving is 5.20% fuel when there was no burner tune up. Fuel could be saved to 9.16% when the burner was tuned up to control excess air. In

addition, NOx and SO2, from flue gas, tend to decrease when the percentage of water in heavy oil increases. micro-explosion micro-explosion NOx

.. 2006 Allouis [1]

1 22 9

7.5 3 micro-explosion OH Kadota Yamazaki [2] .. 1995 Sheng [3] micro-explosions water-in-oil micro-explosion vortex NOx 30 15 .. 2006 Yoshimoto Y. [4] 30 micro-explosion NOx Abu-Zaid [5] direct injection 1 5%, 10%, 15% 20% 3.5 20

1 Hot oil Boiler: Model Circo Herm CH-500 580 kW

1 Hot Oil Boiler water-in-oil 11.8% (W/O, W=11.8%), 18.0% (W/O, W=18.0%) 22.0% (W/O, W=22.0%) SECA (Thailand): Model ST 1500

2 RTD 1 RTD 2

10 1 22

RTD 3 Messtechnik EHEIM GmbH Visit 01-L/LR

2

(1) (2) (3)

TCmQ pw =..

(1)

LHVm

Q

f = .

.

(2)

e

oeSave -

% = (3)

Q

.

wm pC T

.

fm LHV e o

3 0.48% O2 4

150

180

210

240

0 5 10 15 20 25 Water (%)

Q wate

r (kW)

Non Control

Control %O2

3

5 11.8% 81.04% 85.49% micro-explosion 5.20% 9.16% 14.68% 15.01%

1 22 11

0

20

40

60

80

100

120

0 5 10 15 20 25Water (%)

Therm

al eff

icienc

y (%)

Non Control

Control %O2

4

0

5

10

15

20

0 5 10 15 20 25Water (%)

Perce

nt sa

ve (%

)

Non Control

Control %O2

5

6 OH CO2 7 6-7% 8 NOx 0 9

0

3

6

9

12

15

0 5 10 15 20 25Water (%)

O 2 (%

)

Non Control

Control %O2

6 O2

0

3

6

9

12

15

0 5 10 15 20 25Water (%)

CO2 (

%)

Non Control

Control %O2

7 CO2

NOx 0 10 CO 0 CO CO 18.0% 22.0% CO 6-7%

12 1 22

120

130

140

150

160

0 5 10 15 20 25Water (%)

Temp

. Exh

aust

(0 C)

Non Control

Control %O2

8

100

150

200

250

300

0 5 10 15 20 25Water (%)

NOx (

ppm/

0%O 2

)

Non Control

Control %O2

9 NOx

CO2 CO2 7 CO SO2 0 11 SO2

0

500

1000

1500

2000

0 5 10 15 20 25Water (%)

CO (p

pm/0%

O 2)

Non Control

Control %O2

10 CO

900

1000

1100

1200

0 5 10 15 20 25Water (%)

SO2 (

ppm/

0%O 2

)

Non Control

Control %O2

11 SO2

11.8% 5.20% OH 5.20% 9.16%

1 22 13

SECA (Thailand) Co., Ltd. 1. Allouis, C., LInsalata, A., Fortunato L., Saponaro A., and

Beretta F., 2006, Study of water-oil Emulsion in large pilot power plants for fine particle matter emission reduction, Experimental Thermal and Fluid Science 31 (2007) 421426

2. Kadota, T., and Yamasaki H., Recent advances in the combustion of water fuel emulsion, Progess in Energy and Combustion Science 28 (2002) 385-404

3. Sheng H.Z., Chen L. and Wu C.K., 1995, The Droplet Group Micro-Explosions in W/O Diesel Fuel Emulsion Sprays, International Congress and Exposition, Detroit, Michigan

4. Yoshimoto, Y., Performance of DI Diesel Engines Fueled by Water Emulsions with Equal Proportions of Gas Oil-Rapeseed Oil blends and the Characteristics of the Combustion of Single Droplets, Society of Automotive Engineers, 2006-01-3364

5. Abu-Zaid M., Performance of single cylinder, Direct injection diesel engine using water fuel emulsions, Energy Conversion and Management 45 (2004) 697-705

AEC003

14 1 22

A Submicron Electrical Aerosol Detection System

with a Faraday Cup Electrometer

Panich Intra1*, and Nakorn Tippayawong2

1 College of Integrated Science and Technology, Rajamangala University of Technology Lanna, Chiang Mai 50300, Thailand

Tel: 0-5392-1444, Fax: 0-5321-3183, E-mail: [email protected], [email protected] 2 Department of Mechanical Engineering, Chiang Mai University,

Chiang Mai 50200, Thailand Tel: 0-5394-4146, Fax: 0-5394-4145, E-mail: [email protected]

Abstract

Submicron-sized aerosol particles, defined as aerosols with particle diameters less than 1 m, suspended in air have significant effects on the human health, global climate, air quality and processes in various industries such as food, pharmaceutical and medical, electronic and semiconductor industries. Automotive engines have long been recognized as a major source of submicron-sized aerosol particles. Development of aerosol detection and size distribution measurement methods has been primarily motivated by the need to find better means of monitoring and controlling indoor and outdoor aerosols for pollution and process control industry. In this study, a submicron electrical aerosol detection system for measuring particle number concentration in the size range between 1 nm 1 m using electrostatic charge measurement technique was developed. It consists of a size selective inlet, a particle charging system, an ion trap, a Faraday cup electrometer, a signal conditioning and processing system, and an I/O control and human-computer interface. In this system, an aerosol sample first passes through the size selective inlet to remove particles outside the measurement size range based on their aerodynamic diameter, and then pass through the unipolar corona charger that sets a charge on the particles and enter the ion trap to remove the free ions. After the ion trap, the charged particles then enter the Faraday cup electrometer for measuring ultra low current about 10-12 A induced by charged particles collected on the filter in Faraday cup corresponding to the number concentration of particles. Signal current is then recorded and processed by a data acquisition system. A detailed description of the operating principle of the system as well as main components was presented. The performance of the prototype electrometer circuit used in this work was evaluated and compared with a commercial electrometer and good agreement was found from the comparison. Finally, the preliminary experimental testing results were also shown and discussed.

Keywords: aerosol, particle, Faraday cup, electrometer 1. Introduction Detection and measurement of aerosol particles have become an important topic in atmospheric pollution monitoring and source characterization. In recent years considerable interest has been shown to submicron-sized aerosol particles, defined as aerosols with particle diameters less than 1 m, for two main reasons. First, such particles have been associated with adverse health effects in areas of high concentrations, and second, aerosols are believed to have a significant influence on atmospheric quality, climate at a local and global scale and processes in various industries such as food, pharmaceutical and medical, electronic and semiconductor industries [1]. A submicron-sized aerosol particle instruments have been developed to monitoring indoor and outdoor aerosols for pollution and process control industry for this purpose [2, 3]. There are several commercial instruments using various methods of detecting and measuring the size distribution and number concentration of particles. Available instruments include a Scanning Mobility Particle Sizer (SMPS) using electrical mobility of particles [4], a Condensation Particle Counter (CPC) which uses particle growth and optical property [5, 6], an Electrical Aerosol Detector (EAD) which uses electrostatic charge measurement technique [7], and an Electrical Low Pressure Impactor (ELPI) using inertia impaction of particles under low pressure [8]. These commercial instruments are widely used for measuring airborne ultra fine particles and provide high-resolution measurement, but they are very expensive and larges sizes. According to the instruction manual for CPC (Model 3010, TSI Inc), a CPC does not operate in ambient temperatures outside the control range of 10oC to 34oC, and the pump and flow sensor of a CPC cannot control the flow when the pressure at the aerosol inlet, the make up air inlet, or the pump exhaust is too high or too low [6]. In addition, the CPC should be carefully moved in caution to protect the optics contamination from

1 22 15

working fluid like alcohol (C4H9OH) [6].

Figure 1. Schematic diagram of the submicron electrical aerosol detection system.

The movability of instruments should be considered in monitoring airborne aerosol particles. To avoid this problem, an inexpensive detector, suitable for detection of particle number concentration in the submicron size range, was built and experimentally tested in this study. This system is based on unipolar corona charging and electrostatic detection of highly charged particles. A detailed description of the operating principle of the sensor was presented. The performance of the prototype electrometer circuit used in this work as well as the preliminary experimental testing results were also shown and discussed. 2. A Submicron Electrical Aerosol Detection System The following paragraphs give a detailed description of main components of the detection system. Figure 1 shows the schematic diagram of the submicron electrical aerosol detection system, developed in this study. The system is composed of a flow system is regulated and controlled by means of mass flow controllers with a vacuum pump, a size selective inlet to remove the particle outside the measurement range, a particle charger using corona discharge technique to charge the particles, an ion trap to remove the high electrical mobility of free ions after charger, a Faraday cup to collect charged particles, an electrometer for measuring signal current from the Faraday cup, and a computer controlled data acquisition and management system. 2.1 Size Selective Inlet The inertial impactor was used to remove particles larger than a known aerodynamic size, upstream of the system. The aerodynamic particle size at which the particles are separated is called the cut-point diameter. In the impactor, the aerosol flow is accelerated through a nozzle directed at a flat plate. The impaction plate deflects the flow streamlines to a 90o bend. Particles with

sufficient inertia are unable to follow the streamlines and impact on the plate. Smaller particles are able to follow the streamlines and avoid contact with the plate and exit the impactor. The particle collection efficiency of the impactor, E, is determined from [9]

12

501s

p

dE

d

= + (1)

where dp is the particle diameter, and d50 is the particle cut-off diameter at 50% collection efficiency can be calculated by [1]

3

5050

9 Stk4 p a c

Dd

Q C= (2)

where Cc is the Cunningham slip correction factor, is the gas viscosity, D is the acceleration nozzle diameter, Stk50 is the Stokes number for the particle cut-off diameter at 50% collection efficiency, p is the particle density, and Qa is the aerosol flow rate. 2.2 Particle Charger The corona-needle charger used in the present study consists of a coaxial corona-needle electrode placed along the axis of a cylindrical tube with tapered ends [10]. The needle electrode is made of a stainless steel rod 3 mm in diameter and 49 mm length, ended in a sharp tip. The angle of the needle cone was about 9o and the tip radius was about 50 m, as estimated under a microscope. The outer cylindrical is made of aluminum tube 30 mm in diameter and 25 mm length with conical shape. The angle of the cone was about 30o and the orifice diameter was about 4 mm. The distance between the needle electrode

16 1 22

and the cone apex is 2 mm.

Figure 2. Schematic diagram of the Faraday cup. The corona electrode head is connected to a DC high voltage supply, while the outer electrode is grounded. An adjustable DC high voltage power supply is used to maintain the corona voltage difference, typically of the order of 1.0 5.0 kV. The corona discharge generates ions which move rapidly in the strong corona discharge field toward the outer electrode wall. Aerosol flow is directed across the corona discharge field and is charged by ion-particle collisions via diffusion charging and field charging mechanisms. 2.3 Ion Trap The ion trap was used to remove the high electrical mobility of free ions after the charger. As the free ions can potentially reach the detector and ruin the measurement, a trap field is introduced just after the corona charger. The trap field is across the aerosol flow and has a 200 V, and the trap penetration, Ptrap, is given by [1]

2 1

21

ln( / )i

trapa

Z VLP

Q r r= (3)

where Zi is the mobility of ion (equal to 0.00014 m2/V.s for the positive ion), V is the trap voltage, L is the trap length, and r1 and r2 are the inner and outer radii of the electrode, respectively. 2.4 Faraday Cup Figure 2 shows schematic diagram of the Faraday cup. To completely shield the HEPA (high efficiency particulate air) filter collecting the charged particles, external case is made of a stainless steel, and HEPA filter is electrically disconnected from the external case with Teflon stand. The Faraday cup plays a role to prevent electric noise to measure very low current caused by charged particles, which are collected by an internal HEPA filter. If the object of measurement is not shielded completely, noise which is 1000 times of resolutions to

be expected. To transfer charges gathered at the HEPA filter to an electrometer that is outside the faraday cage, BNC connector is connected to HEPA filter. Because material of HEPA filter is conductor such as glass fiber, charges collected in the filter can move to the electrometer through the low noise cable and BNC connector without delay. In the case of existing aerosol electrometer airflow is curved at 90 degrees while air is drifted from sampling probe to the filter. It can become the cause of charge loss. To solve this problem airflow into faraday cage is straighten not to change the direction of the flow and loss the charge. The particle number concentration, Np, is related to the signal current, Ip, at HEPA filter is given by [11]

( )

pp

p p a

IN

n d eQ= (4)

where np is the number of elementary charge units, e is the elementary unit of charge (1.6 10-19 C), and Qa is the volumetric aerosol sampling flow rate into a Faraday cup. The average number of elementary charges carried by particles with diameter, dp, and is given by following equation [1]

2

2( ) ln 1 22p E p i i

p pE

d kT K d c e N tn d

kTK e = +

(5)

where ic is the mean thermal speed of the ions (240 m/s), k is the Boltzmanns constant (1.380658 10-23 J/K, for air), T is the temperature, KE is the constant of proportionality, Ni is the ion concentration, and t is the residence time of the particle charger. For the corona-needle charger, an approximate expression for the Nit product can be derived [10]:

( ) ( )2 21 2 1 2i

i

i

I dNr r r r L eZ V

=+ +

(6)

where Ii is the charging current, d is the distance between the electrode tip and the cone apex, r1 and r2 are the inner and outer radii of a conical frustum, respectively, L is the length of the charging zone, and V is the corona voltage. 2.5 Sensitive Electrometer The schematic presentation of an electrometer circuit design for aerosol detection system is shown in Figure 3. This circuit is a simple current-to-voltage converter, where the voltage drop caused by a current flowing through a resistor is measured. The circuit adopted two cascaded negative feedback amplifiers. Extra component in this circuit is primarily for fine offset voltage adjustment and input/output protection. A 12V power supply capable of providing 100 mA is required. The feedback capacitor and RC low-pass filter were used to reduce high-frequency noise and to prevent oscillations of the amplifier output [12]. In order to avoid expensive

1 22 17

construction, commercially-available low-cost monolithic operational amplifiers were used.

Figure 3. Schematic diagram of the sensitive electrometer circuit.

The commercially-available operational amplifiers used in this circuit is the LMC662, which was designed for low current measurement and featured ultra-low input bias current (2 fA maximum) and low offset voltage drift (1.3 V/oC) [13]. The output voltage, Vo, of this circuit is given by the following equation:

2 3 611 5

o iR R R

V I RR R

+= (7)

where Ii is the input current, R1 and R5 are the input resistors of the first and second amplifiers, respectively, R2 and R3 are the feedback resistors of the first amplifier, and R6 is the feedback resistors of the second amplifier. This circuit gives an output voltage of 10 mV per 1 pA of input signal current. The electrometer circuit was calibrated with a current injection circuit, high-impedance current source [12]. It consists of an appropriately high-standard resistor (10 G) and an adjustable voltage source in the range between 0 5 V. The output current of this circuit can simply be calculated from the Ohms law.

0 2 4 6 8 100

2

4

6

8

10 theoretical this work Keithley 6517A

mea

sure

d cu

rren

t, pA

input current, pA

Figure 4. Performance comparison between the prototype and commercial electrometer.

Figure 5. Schematic diagram of the experimental setup for preliminary testing of the submicron electrical aerosol

detection system. The range of the output current is from 1 pA to 10 pA. It should be noted that the electrometer circuit input was operated at virtual ground potential during calibration and subsequent current measurement. The output voltage from the electrometer circuit was measured and recorded by a highly-accurate digital voltmeter. The voltage reading was then translated into the current measurement. The comparison of measured current from this work and a commercial electrometer, Keithley model 6517A, with high-accuracy current source is shown in Figure 4. It was shown that the measured current was rising linearly as input current increased. Generally, the currents measured from this work were found to agree very well with those measured by the Keithley model 6517A. Very small difference about 5% was obtained. 2.6 Data Acquisition and Processing System The measurement is controlled and data sampled by an external personal computer via RS-232 serial port cable. Software running on an external computer was developed, based on Microsoft Visual Basic programming for all data processing. The software is able to display the particle number concentration. 3. Preliminary Experimental Testing Figure 5 shows the schematic diagram of the experimental setup for preliminary testing of the submicron electrical aerosol detection system. The combustion aerosol generator was used to generate a polydisperse carbonaceous diffusion flame aerosol for this experiment. Stable polydisperse aerosols with particle number concentrations of approximately 1012 1014 particles/m3 were obtained [14]. The particle size obtained by scanning electron microcopy (SEM) was in the range between approximately 10 nm 10 m. Figure 6 shows the particle morphologies of agglomerates obtained from the scanning electron micrograph, taken with a JEOL JSM-6335F Field Emission Scanning

18 1 22

Electron Microscope, operated at 15 kV and magnification of 5,000X.

Figure 6. Scanning electron micrograph of sampling particle from the generator.

The particles were first dried with the diffusion drier. Thus, any remaining water was removed. Before aerosol particles entering the system, the particles were diluted and mixed with clean air, which had been filtered through a HEPA filter, in the mixing chamber. The system was operated at aerosol flow rate in the range of 1.0 4.0 L/min. To reduce errors due to time variations in the aerosol concentrations, repeat measurements were commenced at least 5 min after the introduction of the aerosol into the measurement system. In this paper, four different operating conditions of the aerosol flow rate were preliminary experimental tested on the particle number concentration measurements of the system. Variation of aerosol flow rate was carried out by adjusting the inlet mass flow controller in the range of 1.0 to 4.0 l/min and the operating pressure was about 1000 mbar. Figure 7 shows variation of measured particle number concentration and signal current with aerosol flow rates. The measured signal current and the particle number concentration were found in the range of approximately 90 700 pA and 3 7 1013 particles/m3, respectively. It was found that an increase in the aerosol flow rate resulted in an increase in measured signal current corresponding to the particle number concentration because the signal current was approximately proportional to the aerosol flow rate. 4. Conclusions and Future Work The system for detecting the number concentration of submicron-sized aerosol particles with a Faraday cup electrometer has been presented and described in this paper. The detecting method was based on unipolar corona charging and electrostatic detection of highly charged particles. It was able to detect particle number concentration in the submicron size range. A prototype of the system has been constructed and evaluated. Preliminary experimental testing results obtained were very promising. It was demonstrated that the system can be used in detecting the number concentration of the particles. The following paragraphs give specific recommendations for further research work on both the

theoretical and experimental parts of the detector development.

1 2 3 40.0

2.0x10-10

4.0x10-10

6.0x10-10

8.0x10-10

1.0x10-9

parti

cle

curr

ent,

A

aerosol flow rate, L/min

1010

1011

1012

1013

1014

parti

cle

num

ber c

once

ntra

tion,

par

ticle

s/m

3

Figure 7. Variation of measured particle number

concentration and current with aerosol flow rates.

There are various techniques and devices exist for generating aerosol samples to testing and calibration of any instrument that measures aerosol particles. One of the most widely used techniques of generating monodisperse aerosol particles is by using the Tandem DMA method. The main advantage of this method is the wide range of particle sizes it can generate. Further research, may involve the Tandem DMA.

Calibration and comparison of the instrument with other particle measuring devices such as SMPS, CPC, EAD, and ELPI should be conducted further.

In order to measure transient behavior of airborne particles, such as those found in automotive exhaust gas, the time response of the instrument should be further improved.

Acknowledgment Financial support from the Thailand Research Fund (TRF) is gratefully acknowledged. References 1. Hinds, W. C., 1999. Aerosol Technology, John

Wiley & Sons, New York. 2. Intra, P. and Tippayawong, N., 2003. Particle Size

Analyzers. Journal of the Scientific & Technological Research Equipment Centre, Vol. 11, 156-170. (in Thai)

3. Intra, P. and Tippayawong, N., 2007. An Overview of Aerosol Particle Sensors for Size Distribution Measurement. Maejo International Journal of Science and Technology, Vol. 1, No. 2, pp. 120 - 136.

4. TSI Incorporated, 2006. Operation and Service Manual, Revision L, for Scanning Electrical Mobility SizerTM (SMPSTM) Spectrometer, Model 3936, Minnesota.

1 22 19

5. Agrawal, J.K. and Sem, G.J., 1980. Continuous Flow, Single-particle-counting Condensation Nucleus Counter. Journal of Aerosol Science, Vol. 11, 343 - 357.

6. TSI Incorporated, 2002. Instruction Manual, Revision F, for Condensation Particle Counter, Model 3010, Minnesota.

7. Johnson, T., Kaufman, S. and Medved, A., 2002. Response of an Electrical Aerosol Detector based on a Corona Jet Charger, 6th International. ETH Conference Nanoparticle Measurement, 19 - 21 August, Zurich, Switzerland.

8. Keskinen, J., Pietarinen, K. and Lehtimaki, M., 1992. Electrical Low Pressure Impactor. Journal of Aerosol Science, Vol. 23, pp. 353-360.

9. Intra, P., 2008. An Inertial Impactor for Submicron-Particle Separation. Chiang Mai University Journal of Natural Science, under 1st review.

10. Intra, P., and Tippayawong, N., 2006. Corona Ionizer for Unipolar Diffusion Charging of Nanometer Aerosol Particles, Proceeding of 29th Electrical Engineering Conference, Pattaya, Thailand, 9 10 November, pp. 1177 1180.

11. Intra, P. and Tippayawong, N., 2008. An

Electrostatic Sensor for Nanometer-Sized Aerosol Particles Detection, Asia-Pacific Symposium on Applied Electromagnetics and Mechanics, 24 - 25 July, Bangkok, Thailand.

12. Intra, P., and Tippayawong, N., 2007. An Ultra-Low Current Meter for Aerosol Detection. Chiang Mai University Journal of Natural Science, Vol. 6, No. 2, pp. 313 320.

13. National Semiconductor Corporation, 2003. LMC662 CMOS Dual Operational Amplifier Data Sheet.

14. Cleary, T.G., Mulholland, G.W., Ives, L.K., Fletcher, R.A. and Gentry, J.W., 1992. Ultrafine Combustion Aerosol Generator. Aerosol Science and Technology, Vol. 16, pp. 166-170.

AEC004

20 1 22

Performance Evaluation of Incinerator for Community-Based

Solid Waste Management

1 .. 2 .. 3 50200

E-mail : [email protected] [email protected] [email protected]

2 184 691 (NOx) 134 (ppm) (SO2) 20 % 99.95% 519.06 .. 2550 .. 2551 39,192 47,323 1.

2.

20

1 22 21

1

[1] Natural Draft

4 8 10

2

50 [2] 2.37 %

3

32.77% 57.18%

10.05%

9.02%

1.03%

1.34%

2.37%

22 1 22

3.

3.1 Thermocouple type K 8 8 Chanel Thermo Couple Input ADAM 4018 Lab View Portable Flue Gas Analyzer Testo 350 XL

3.2

3.3 0:100 20:80 40:60 50:50 60:40 200

3.4 0:100 20:80 40:60 50:50 60:40

4

4.

4.1

5 8.30 10.30 27 .. 2551 307 10.30 12.30 27 .. 2551 243 137.5 500

5

free convection 5,193.30 (W) 1,372.8 (W) 1848.97 (W) 423.44 1245.27 (W) 302.82 (W)

0100200300400500600700800900

1000

8:30:3

7

10:10

:22

11:50

:07

13:29

:52

15:10

:56

16:50

:41

(o C

)

.. .. .. 2550 2550 2551 ( ) ( ) ( )

1 5,212 5,567 4,821 2 9,933 14,000 7,634 3 7,914 3,710 584 4 2,365 1,122 1,553 5 744 3,200 2,363 6 3,880 5,670 5,500 7 2,630 4,497 3,123 8 3,622 3,847 1,776 9 3,798 3,150 8,677 10 1,548 2,560 3,161

41,646 47,323 39,192

1

1 22 23

4.2 183

6

4.3

7

4.4

Natural Draft

Natural Draft [3] 519.06

8

4.5 99.95 % 10 % 21 % 40 %

9

0

50

100

150

200

0:100 20:80 40:60 50:50 60:40

1

(kg.)

183 kg.160 kg.

133 kg. 120 kg. 120 kg.

0100200300400500600700800

0:100 20:80 40:60 50:50 60:40

(o C

)

691 675 644573

372

694 689 710590

415

9797.5

9898.5

9999.5100

0:100 20:80 40:60 50:50 60:40

(%)

99.95

99.70

99.79

98.4998.08

0100200300400500600

0:100 20:80 40:60 50:50 60:40

(k

W) 519.06 512.72 493.24431.58

273.09

24 1 22

40 % 20 % 40 %

4.6

[4] (NOx) (SO2) (HCL) (NOx) 100 200 ppm (SO2) 15 ppm 50:50 22 0-5%

2 ppm

(CO)

(NO) 600 100 ppm 400 ppm (NOx) 100 200 ppm

10 CO NO

5. 184 691 519.06 137.5 512 600 6.

: CO NO NO2 NOx SO2

0:100 64 134 0 134 0 20:80 400 200 0 200 0 40:60 675 198 0 198 0 50:50 756 178 0 178 15 60:40 1089 127 0 127 0

02004006008001000

120014001600180020002200240026002800

200 300 400 500 600 700 800 900(oC)

(pp

m)

CONO

1 22 25

[1] .

NFI-02 (2008) [2]

, /,( 1 2548)

[3] The Engineering Toolbox, Air Flow and Velocity due to Natural Draft, http://www.engineeringtoolbox.com/natural-draught-ventilation-d_122.html

[4] . . 114 63 7 .. 2540

AEC005

26 1 22

Optimal Placement of Biogas Plant from Cow Dung by Geographic Information System

1* 1 2

1 . . 12121 0-2564-3001 3053 0-2987-6800 * [email protected]

2 . . 12121 0-2564-3001 3053 0-2987-6800 [email protected]

(Geographic Information System: GIS) , , 15 150 111,189 262 -CO2/

Abstract

In this study, the optimal placement of biogas plant from cow dung for members of co-operative was studied to maximize the benefit of plant with consideration of transportation costs, biogas production and environmental effects. Geographic information system (GIS) was applied to evaluate the interested locations of biogas plants where are high household density area, high cow density area, dairy co-operative, and location of local community leader. The scope of this study covered 15 households with 150

cows around the dairy co-operative, located in Lamprayaklang Reform Land, Saraburi Province. According to the result, the dairy co-operative is the optimal placement of biogas plant. The quantity of cows at the dairy co-operative is lower than that of cows at the other locations but the transportation cost at the dairy co-operative is the lowest. The profit at the selected site is 111,189 baht per year and the greenhouse gas can be reduced up to 262 tons CO2 equivalent per year.

1.

2548 2542 [1] [2]

1 22 27

[3] [4] [5] 2. 2.1 20 19,856 3,551,246 15 150 10 ( 1 ) , ( 2 ) , ( 3 ) ( 4 ) 2

2.2 (Geographic Information System: GIS)

[6] 1

1 GIS 2.3

(Global Positioning System : GPS) (Geographic Information System: GIS)

(Data Update)

(Data Analysis)

(Output)

(Data Input)

(Data Preparation)

(Objective)

(Spatial Data)

(Attribute Data)

28 1 22

3

21

4

DE

G

F H

AB

C

IJ

K

L

NM O

2 A-O 1-4 2.4 1 0.04 10 [7]

=

=N

iiijj CdTC

1)4.0( (1)

TCj = j dij = j () ci = i N = dij (Geographic Information System: GIS) 2.5 (BGi) 2 0.49

1 21.5 MJ 0.46 kg [8]

ii CBG = 49.0 (2) 2.6 3 3

=

N

iji TCBGMax

1)13.18( (3)

1 22 29

3.

2 3 223,735 262 -CO2/

2

()

()

1 152,222 71,513 2 119,496 104,239 3 4

112,546 115,521

111,189 108,214

4.

111,189 262 -CO2/

3

(Ci)

(Ci) (BGi)

(dij)

30 1 22

1. Maeng H., Lund H., and Hvelplund F., 1999. Biogas

plants in Denmark : technological and economic developments. Applied Energy, Vol. 64, pp. 195-206.

2. Yilmaz I., 2008. A case study for mapping of spatial distribution of free surface heave in alluvial soils (alvo, Turkey) by using GIS software. Computer and Geosciences, Vol. 34, pp. 993-1004.

3. Gunnarsson C., Vagstrom L., Hansson P.A., 2008. Logistics for forage harvest to biogas production-Timeliness, capacities and costs in a Swedish case study. Biomass and Bioenergy, In journal homepage: www.elsevier.com, Accepted 17 March 2008.

4. Singh J., Panesar, B.S., and Sharma, S.K., 2007. Energy potential through agricultural biomass using geographical information system-A case study of Punjab. Biomass and Bioenergy, In journal homepage: www.elsevier.com, Accepted 1 October 2007.

5. Voivontas D., Assimacopoulos D., Koukios E.G., 2001. Assessment of biomass potential for power production: a GIS based method. Biomass and Bioenergy, Vol. 20, No. 2, pp.101-112.

6. , 2549, (GIS), ...

7. Omer A.M., and Fadalla Y., 2003. Biogas energy technology in Sudan. Renewable Energy, Vol. 44, No. 28, pp. 499-507.

8. , , 1, ,, 11-13 2548, 1-6.

AEC006

1 22 31

DME Analysis of Energy Release of CI Engine Operating on DME

* ,

. 10330 0-2-218-6607 0-2-252-2889 *E-mail : [email protected]

DME (DI-Methyl Ether) , DME DME DME Abstract

DME (DI-Methyl Ether) is a clean alternative fuel, suitable for compression ignition engine, which can replace diesel fuel without black exhaust smoke. However, since DME contains lower heating value than diesel fuel, its torque at full load becomes lower as well. A study on combustion energy concluded the following information: Energy Release derived from pressure data in small direct injection engine (DME used as primary fuel), shows the ignition delay is short and rates of change in pressure and energy release are high. The data in this study is potentially significant development towards the higher efficient application of DME as a substitute fuel.

1.

DME (Di-Methyl Ether)

DME SOx DME CI DME CI DME DME 2. 2.1

32 1 22

2.1.1 CI CI

2 (direct-injection system, DI system) (indirect-injection, IDI system) 2 (prechamber) (main chamber) 2.2 CI

1

dtdUhm

dtdVP

dtdQ

iii

=+ (1)

dtdQ

dtdVP

im

ih i U

1

3. (Di-Methyl Ether DME) DME DME

DME DME -25C 6 bar

DME 2 syngas (methanol synthesis) DME methanol dehydration

DME (chemical formula) 33OCHCH C2H6O (oxygen) DME (Liquefied Petroleum Gas LPG) DME DME (soot) energy content

1

DME

4. 4.1

1 22 33

4.1.1 KUBOTA RT 140 2 Kubota RT 140 Single Cylinder Direct Injection 97 mm.(Bore) 96 mm. (Stroke) 709 CC. 10.3 kW / 2400 rpm 49.0 Nm /1600 rpm 18:1 21.57 MPa

2 4.1.2 (Dynamometer)

(Hydraulic Dynamometer) (Water Brake) 3

Hydraulic Dynamometer Redman Heenan International

Company, England Froude Hydraulic

Dynamometer (DPX2) Resolution 0.1 kg. 0.03525 m. 150/7500 CV/rpm, (1 CV =

0.986 hp)

3 Dynamometer 4.1.3 Orifice 4.1.4 Type K (Chromel-Alumel, CA) 0.65 . , , 4.1.5 proximity inductive (pulse meter) proximity

(flange) 4.1.6 DME 3MPa Vapor Lock 4.1.7

Piezoelectric Pressure Transducer Pressure Transducer AVL GU12P Pressure Transducer KISTLER 607C1

DEWE-Book Combustion Analyzer Version6 real-time 4.1.8 . 4.1.9 60 2 4.2 1300 3.2kg7.1kg ()

70 oC 3.2kg 7.1kg 5. 7.1kg 3.2 kg 2 3

34 1 22

Main Chamber Pressure @ 1300 rpm

0

20

40

60

80

-20 0 20 40 60

Crank Angle (Degree)

Pre

ssur

e (B

ar)

Load3.2 Kg

Load 7.1 Kg

2 1300 rpm

3 1300 rpm

45

Heat Release Rate

-10

0

10

20

30

40

50

-40 -20 0 20 40 60


dQ/d

CA

(J/D

egre

e)

Load 3.2 Kg

Load 7.1 Kg

4 1300 rpm

5 1300 rpm

6

7

Ignition Delay

0

2

4

6

8

10

Igni

tion

Del

ay C

.A (D

egre

e)

Load 3.2 KgLoad 7.1 Kg

6 1300 rpm

00.1

0.20.3

0.40.5

0.60.7

-50 0 50 100


Xb

Load 3.2 Kg

Load 7.1 Kg

7 1300 rpm

@ 1300 rpm

0

0.5

1

1.5

2

2.5

3

-30 -20 -10 0 10 20Crank Angle (Degree)

dmf/dCA (mg/Degree)

Integrated Heat Release @ 1300 rpm

-100

0 100

200

300

400

500

600

700

800

-40 -20 0 20 40 60 80Crank Angle (Degree)

Q (J)

Load 3.2 Kg Load 7.1 Kg

1 22 35

6. , , Premix Burn 7. , 8. 1 Gary L. Borman and Kennth W. Ragland, Combustion Engineering, Mcgraw Hill, Singapore, 1988 2 Heywood, J. B., Internal Combustion Engine Fundamentals. Singapore, Mcgraw Hill, 1988. 3 RT140, ,

, .

AEC007

36 1 22

Feasibility Study of Biomass Quality for Wood Pellets

*

114 12121 0-2564-6500 0-2564-6401 [email protected]

19.3 MJ/kg 4 2,000 17,000 mg/kg 2.1 3.8 wt.-%

Abstract

The continuous increase in oil price and the awareness of global warming have recently brought interest in alternative energy. Biomass is one of the resources for alternative energy that has been utilized in several countries, especially in Europe, where wood pellets have been widely used. For Thailand, where agriculture is one of the significant driving forces for the production of the country, biomass is inevitably been paid a special attention due to the abundance of wasted biomass from agriculture and food industry. Although there are some researches on the production of wood pellets and the design of pellet

machines, there is little information about the properties of some raw materials. Those properties will affect the pellet quality, the design of pellet machines, and the design of energy conversion system. This project is therefore initiated to preliminarily study the quality of available raw materials that have potential to be used as fuels, including Para-rubber wood, palm leaves, palm trunks, and palm empty-fruit-bunches. From the study, it can be said in general that Para-rubber wood, palm leaves, palm trunks, and palm empty-fruit-bunches contain chemical composition that may cause high amount of ash content, hard deposit, emission, and corrosion of machine components. In addition, the calorific values of these raw materials are found to be lower than the standard value. For chemically-treated Para-rubber wood, a large amount of heavy metals are found, which will cause high ash content and emission. The designs of systems that deal with these raw materials, therefore, need to pay a special attention to the quality of these raw materials. Although the use of wood pellets has been successful in some other countries, the difference in raw materials will be a critical variable in choosing appropriate technology to utilize biomass and will determine its success.

1. (Solid biomass)

1 22 37

(Pelletization) (Pellet) (Wood pellet) 1

1:

Hamelinck [1] (Closed carbon cycle) CO2 Schuller [2]

1

1 * Parameter Effects

Water content storability, calorific value, losses, self-ignition

Calorific value fuel utilization, plant design Chlorine (Cl) HCl, dioxin/furane emissions, corrosion

in superheaters Nitrogen (N) NOX, HCN, and N2O emissions Sulfur (S) SOX emissions Potassium (K) corrosion in superheaters, reduction of

ash melting point Magnesium (Mg), Calcium (Ca), Phosphorus (P)

raising of ash melting point, effect on pollutant retention in ashes and use of ashes

Heavy metals pollutant emissions, use or disposal of ashes

Ash softening behavior operational safety, level of pollutant emissions

Ash content particle emissions, costs for use or disposal of ashes

Fungi spores health risks during fuel handling Bulk density transport and storage expenditures,

logistical planning Unit density Combustion properties (specific heat

conductivity, rate of gasification) Particle size distribution

pourability, bridge-building tendency, operational safety during fuel conveying, drying properties, dust formation

Share of fines bulk density, transportation losses, dust formation

Durability quality changes during transshipment, disintegration, fuel losses

* Source: Hahn [3] 2. 2

38 1 22

2

()

. , , .

()

. , , .

, . , .

* , . , .

* , . , .

** . , . , .

* 3 ** 8 2 6 7

2

3

4

5

6

7

3. 1. Mercury, Potassium, Copper, Zinc, Arsenic, Chromium, Lead, Cadmium: AOAC (2000 ), 999.10 2. Hydrogen, Nitrogen, Sulfur: CHNS analyzer 3. Water content: 4. Bulk density: 5. Gross calorific value (GCV) High heating value (HHV): Bomb Calorimeter ASTM D240 6. Net calorific value (NCV) Low heating value (LHV): (1) Obernberger Thek [4]

1 22 39

=

100

..1447.2*02.18*

200

..

100

..*447.2

100

..1....

bdHX

bdHX

bwWX

bwWXbdGCVbwNCV

(1)

..bwNCV : Net calorific value [MJ/kg, wet basis]

..bdGCV : Gross calorific value [MJ/kg, dry basis) ..bw

WX : Water content [wt-%, wet basis] ..bd

HX : Hydrogen content [wt-%, dry basis] 7. wet basis (w.b.) dry basis (d.b): wet basis wet basis dry basis (2)

=

100

w.b.WX1

w.b.Xd.b.X (2)

..bdX : Content [wt-%, dry basis] ..bwX : Content [wt %, wet basis]

..bwWX

: Water content [wt-%, wet basis] 3. 2 1. DIN 51731: DIN 5173 3

3 DIN 5173

/ * (w.b.) Mercury (Hg) 0.05 mg/kg Potassium (K)** N/A mg/kg Copper (Cu) 5 mg/kg Zinc (Zn) 100 mg/kg Arsenic (As) 0.8 mg/kg Chromium (Cr) 8 mg/kg Lead (Pb) 10 mg/kg Cadmium (Cd) 0.5 mg/kg Nitrogen (N) 0.3 wt-% Sulfur (S) 0.08 wt % Ash Content 1.5 wt % NCV 17.5 MJ/kg

* NCV ** Potassium 2. : Obernberger Thek [4] Potassium, Copper, Zinc, Lead NCV 4

4

(d.b.) Potassium (K) mg/kg 493 302 1180 Copper (Cu) mg/kg 1.1 0.7 2.7 Zinc (Zn) mg/kg 13.2 9.3 25.4 Chromium (Cr) mg/kg 0.6 0.1 3.3 Lead (Pb) mg/kg 0.43 0.07 2.19 Cadmium (Cd) mg/kg 0.14 0.06 0.20 Nitrogen (N) mg/kg 2200 2000 6400 Sulfur (S) mg/kg 278 52 1922 Ash Content mg/kg 5100 1700 16100 NCV MJ/kg 19.0 18.6 19.4 4. 5 5

(dry basis)

(d.b.)

Potassium (K) mg/kg 2158 7008 17207 17094 Copper (Cu) mg/kg 1.65 3.00 4.59 15.92 Zinc (Zn) mg/kg 5.83 12.61 22.05 200.28 Chromium (Cr) mg/kg 0.11 11.49 65.88 40.53 Lead (Pb) mg/kg 0.40 3.91 7.56 0.67 Cadmium (Cd) mg/kg 0.11 0.10 0.17 0.09 Nitrogen (N) wt % 0.62 1.54 2.47 1.55 Sulfur (S) wt % 2.29 2.20 3.78 2.05 Ash Content wt % 2.30 2.99 6.29 4.53 NCV MJ/kg 14.8 14.6 14.4 19.3

40 1 22

5. Potassium Sulfur Potassium 2,000 17,000 mg/kg (d.b.) Sulfur 2.1 3.8 wt.-% (d.b.) Nitrogen Chromium Ash content Nitrogen 1.5 2.5 wt.-% (d.b.) Chromium 11 66 mg/kg (d.b.) Ash content 3.0 6.3 wt.-% (d.b.) Arsenic Lead Copper Lead Copper Zinc Net calorific value 14.4 14.8 MJ/kg (d.b.) Net calorific value 19.3 MJ/kg (d.b.) Zinc Chromium Lead Potassium Ash melting point [Obernberger nd Thek, 2003] Sulfur Ash content, Nitrogen, 6.

2550

1. Hamelinck, C. N., Suurs, R. A. A., and Faaij, A. P. C., 2005,

International Bioenergy Transport Costs and Energy Balance, Biomass and Bioenergy, Vol. 29, pp. 114 134.

2. Schuller, A. L., 2004, Developing a Wood Pellet Fuel Sector in South Yorkshire, Connesss GmbH, Austria, Econergy Ltd., Great Britain, South Yorkshire Forest Partnership, Great Britain, pp. 134.

3. Hahn, B, 2004, Existing Guidelines and Quality Assurance for Fuel Pellets, Pellets for Europe, Deliverable 29, UMBERA.

4. Obernberger, I. and Thek, G., 2003, Physical Characterization and Chemical Composition of Densified Biomass Fuels with regard to their Combustion Behaviour, Biomass and Bioenergy, Vol. 27, pp. 653 669.

.

AEC008

1 22 41

:

Experiment Test of Biodiesel in Single Cylinder Diesel Engine: Performance, Black Smoke and Long Term Evaluation

*

114 . . . 12120 0-2564-6500 4742, .0-2564-6403, * [email protected]

300 14 300 Abstract At the present, biodiesel has been widely promoted in Thailand especially in agriculture section. To reduce the use of petroleum diesel and the budget for energy import are key factors for promotion of biodiesel. Single cylinder diesel engines, which have been use for agriculture such as water pump, electric generator and agricultural machinery, is the first target of promoting. Hence, this paper aims to investigate engine performance, black smoke capacity, fuel consumption and effects of long term usage when fueled 14 hp single cylinder diesel

engine fueled with biodiesel. The comparison with fossil diesel shows little difference in torque and power, small increase on fuel consumption but obvious decrease on black smoke. Nonetheless, the 300 hr durability test with water pump application reveals some problems in fuel filter and injector. 1.

"transesterification" [1]

14 300

42 1 22

2.

RT 140 1 2

2 ( 1 2) TECHNO TEST 495/01 ( 3) 300

1 RT 140 [2]

4 1

x

97 x 96 .

709 cc.

14 /2400 hp/ (10.3 /2400 kW/)

12.5/2400 hp/ (9.2/2400 kW/)

12.5/2400 hp/ (9.2/2400 kW/)

18 : 1

5.0 kg-m/1600

2

1. Water Content ASTM D 6304 754.75 ppm

2. Acid Value ASTM D 664 0.27 mg KOH/g

3. Oxidation Stability EN 14112 11.01 Hour 4. Carbon Residue ASTM D 4530 0.01328 %wt 5. Gross Heat ASTM D 240 38.20 MJ/kg 6. Cloud Point ASTM D 2500 19.4 oC 7. Density ASTM D 4052 0.84695 g/cm3

8. ASTM Color ASTM D 1500/156

0.8 -

9. Pour Point ASTM D 97 18.0 oC 10. Flash Point ASTM D 93 165.0 oC 11. Kinematic viscosity at 40 oC ASTM D 445 4.518 mm

2/sec

1

2

1 22 43

3 TECNOTEST 2.1.

RT 140 300, 500, 1,500 2000 80% (Power) (Torque) (1), (2) (3)

VIP .Gen = (1)

GenEngine

VIP = (2)

NP

Engine2

60= (3)

.GenP () I ()

V () EngineP () (-)

N () Gen

0.8

Full load-Full Throttle 2,400 200 1,400 2.2.

75% ( 4) 2,400 22 300 300

4

3.

5 6

7 (Heating value) [3]

8 [4]

44 1 22

5

6

7

8

300

9 10 300

9 ()

10 ()

1 22 45

11 300 4.

300

2,000

MT-B-49-END-07-012-I: 1. Magin Lapuerta, Octavio Armas, Jose Rodriguez-Fernandez,

Effect of biodiesel fuels on diesel engine emissions, Process in energy and combustion science 34 (2008) 198-223.

2. RT

3. MT-B-49-END-07-012-I

4. Yamane K., Ueta A., Shimamato Y., Influence of physical and chemical properties of biodiesel fuels on injection, combustion and exhaust emission characteristics in a direct injection compression ignition engine, Int. J. Engine Vol.2 No.4 (2001) 249-261.

.

AEC009

46 1 22

-

Experimental Studies of Jatropha-Gasoline Blended Fuel in Carburetor System Motorcycle

1* 2 3

10900 0-2942-8567 503 0-2940-5823

Nattawut Sasitorn1* Apithep Suwongkrua2 and Taweedej Sirithanapipat3

Department of Mechanical Engineering, Faculty of Engineering, Kasetsart University, Bangkhen, Bangkok 10900, Thailand

Email: [email protected]*, [email protected], [email protected] 3

- 91 91 5 91 4 2.49% 5.35% 6.31% THC CO 91

Abstract

This paper presents the research on jatropha oil. The research aims to verify the possibility of using the mixed-fuel between jatropha oil and gasoline. Gasoline used in the research has a octane number of 91. The ratio of mixed-fuel is 5% jatropha oil and 95% gasoline. The physical properties of the jatropha oil and mixed-fuel are presented. The comparisons of using this mixed-fuel are carried on under the aspects of performance, fuel consumption, emission and wearing. The tested vehicle is the 4-stroke carburetor engine motorcycle. The mixed-fuel acidity and viscosity exhibit insignificant change after the several weeks period. No separation of the jatropha oil and gasoline is detected. After the road test, using Bangkok driving pattern, the engine is able to operate with the mixed-fuel. The maximum torque and maximum power of the mixed-fuel are 2.49% and 5.35% less than the pure gasoline respectively. Fuel consumption of the mixed-fuel is 6.31% higher. Emissions on THC and CO are less than the standard as well. Physical wearing on parts is not different from the engine using gasoline octane 91. The long term effect of mixed-fuel to engines is also under investigated. Keywords; Blended fuel performance/Jatropha oil/Gasoline engine

1. 1*, 2 Department of Mechanical Engineering, Faculty of Engineering, Kasetsart University 3 Asst. Prof. of Mechanical Engineering, Faculty of Engineering, Kasetsart University

1 22 47

1,593,685 [1]

25-30% 9,470 kCal/kg 10,600 kCal/kg [2] 6,696.3 kCal/kg

- 5 91

2. 2.1

1 3

(1) (Screw press) 25

(2) 3

2.2

1

1 [3] Fatty acid Composition (%)

Saturated components 21.7 Plamitic acid ( 23216 OHC ) 14.7 Stearic acid ( 23618 OHC ) 6.9

Un Saturated components 78.4 Oleic acid ( 23418 OHC ) 42.4

Linoleic acid ( 23218 OHC ) 35.2 2 [2]

Property Method Unit Jatropha oil Specific gravity ASTM D4052 - 0.9186 Flash point JIS-K-2265 oC 240 Carbon residue JIS-K-2270 % 0.64 Distillation JIS-K-2254 oC 295 Kinematic viscosity JIS-K-2283 cSt 50.73 Sulphur ASTM D3120 % 0.13 Calorific value ASTM D240 Kcl/kg 9,470

30C (Kinamatic Viscosity) ASTM D445 (Acid Value) 10

2.3

(Blending) 91 (.) 30C 2

48 1 22

(1) 91 (2) - 5

2.4 Honda

Wave R 125 (Run-in) 1,000 . Chassis Dynamometer

3 Wave 125R 4 OHC

124.9 x 52.4 x 57.9 . 9.3 : 1 CDI 4.0 5

2

2.4 2

5 .2130-2545 IS:10000 Indian Standard Institution , JIS Japanese Industrial Standard ECE R40 Vehicle Emissions Standards of Europe

(1) 1,000.

( 2 ) (Chassis Dynamometer) (Chassis Dynamometer) (Driving Cycle) (Constant Volume Sampling : CVS)

(Run-in) 1,000

Run-in 1,000 .

100 ., 200 ., 500 ., 1,000 .

Chassis Dynamometer

3

1 22 49

4 3. 3.1 -

4 (ASTM D445)

Sample Period (s) Viscosity (cSt) 423.69 43.00 91 42.45 0.61 95:5 47.01 0.68

4

5% 10 5

Viscosity @5%

0.6

0.64

0.68

0.72

0.76

0.8

0 1 2 3 4 5 6 7 8 9 10Period (week)

Visco

sity (

cSt)

5 5%

5 Sample Acid Value (%)

4.42 91 0.31 95:5 0.42

5

(Acid Value) 6

Acid Value @5%

0.010.410.811.211.612.012.412.81

0 1 2 3 4 5 6 7 8 9 10Period (Week)

Acid

value

(%)

6 5%

6

Test Item

Sample

Method (ASTM)

Unleaded Gasoline 91

Gasoline Jatropha Blended

5% Acid Value - 0.31% 0.42% Viscosity D445 0.61 cSt 0.68 cSt

Density vis(700) D4052 0.7429 0.7466 API @60F D4052 58.9 56.82

SG API @60F D4052 0.7432 0.7514 Distillation IBP 10% Evaporated 50% Evaporated 90% Evaporated End Point Residue

D86

35.9 C 54.5 C 95.9 C 162.9 C 195.6 C 0.8 %Vol

34.7 C 55.5 C 94.5 C 170.0 C 198.2 C 5 %Vol

Research Method (RON)

D2699 91.6 90.6

Motor Method (MON) D2700 83 82

6

(Acid Value) (Viscosity) 91 (Distillation) - 5% Distillation Residue

Octain Number Research Method (RON) Motor Method (MON)

50 1 22

91 (RON 90.6-94.6 MON 79.6-83.6) 3.2 - 5%

Honda wave 125 1,000

1.

2.

3.

4. 200 1,000 3.3

1,000 Chassis Dynamometer

5.00

6.00

7.00

8.00

9.00

10.00

0 1000 2000 3000 4000 5000 6000 7000 8000 9000Engine Speed [1/min]

Total

Torqu

e [Nm

]

Gasoline 91Jatropha blend 5%

Max Torque 8.82 @4200Max Torque 8.60 @4200

7 91 5%

91 8.82 4,200 8.60 2.49

6,000 5.35 8

1.00

1.502.00

2.503.00

3.50

4.004.50

5.005.50

6.00

0 1000 2000 3000 4000 5000 6000 7000 8000 9000Engine Speed [1/min]

Whee

l Pow

er [kW

]

Gasoline 91Jatropha blend 5%

Max Power 5.700 @7200

Max Power 5.395 @7200

8 91 5%

42.0439.16

43.74 42.06 41.65

47.4944.4143.7

05

101520253035404550

Phase 1 Phase 2 Phase 3 Average

Fuel

Cons

umpti

on (k

m/l)

91-

8

- 6.31 (Specific Heat)

1 22 51

020406080

100120140160180200220240260280300

91 2.65 290 89.17

- 5%

0.7 88.33 93.17

(CO)

(dB)

9

0.05.0

10.015.020.025.030.035.040.045.0

91- 5%

91 1.130 0.256 12.207 38.362

- 5%

0.495 0.354 9.290 43.767

THC (g/km) NOx (g/km) CO (g/km) CO2 (g/km)

10

- THC CO

4 1,000

Chassis Dynamometer

11

12

13

91 13

12

11

5. 1.

95:5

2. 95:5

3. 91 6.31%

4.

Gasoline 91 Jatropha blend 5%

Jatropha blend 5% Gasoline 91

52 1 22

6.

-

7. [1] , , http://www.doeb.go.th/information.htm (accessed on July 2007). [2] , . . . , 2525 [3] , , Laurent Vaysse, . . 43. 641-648. , 2548

AEC010

1 22 53

Feasibility Study of Anhydrous Ethanol Blended with Gasoline for Small Aircraft Engine

*

114 . . . . 12120

0-2564-6500 4700, .0-2564-6403 [email protected]

10 20 E10 ( 91/95) E20 20 Rotax 912S 2 STOL CH 701 Rotax 912S AVGAS 100LL 95 ( 95) E10 ( 95) E20 60 70 ( E60 E70 ) 95 Rotax 912S E10 ( 95) E20 (> 5,000 ) E20 ( 95) E10 ( 95) E60 E70 Rotax 912S

5,800 Abstract From the current energy crisis that has driven the price of fossil fuel around the world, there is a great interest to seek alternative fuel. One of the attractive candidates is ethanol, which does not require complicated processing technology, and can use existing infrastructure from ethanol industry. In particular, the strong and clear supporting governmental policy toward ethanol utilization as transportation fuel in the forms of E10 (octane 91 and 95) and E20 (octane 95) is set forth to reduce 20 million liters/day gasoline consumption. The present study evaluates the feasibility to use anhydrous ethanol in Rotax 912S engine for 2-seaters small aircraft STOL Ch 701. This Rotax engine is certified to fuel with AVGAS 100LL or ULG95 (unleaded gasoline with octane 95). Engine performance is measured with the force sensor when the engine is attached to the propeller while the fuel consumption and emission are monitored for various fuels, comprising of ULG95, Gasohol E10 (Octane 95), Gasohol E20, self-blend E60 and E70. Since ULG95 is used as control set, the engine is tuned with ULG95 prior to being tests with other fuels. The results show that Rotax 912S engine can be fueled with E10 and E20 of both Octane 95 without statistically significant loss but higher fuel consumption at high speed (> 5,000 rpm). The corresponding emission from E20 is different from E10 or ULG95. On the other hand, E60 and E70 cannot be used n Rotax 912S engine since the engine cannot reach high speed of 5,800 rpm.

54 1 22

1. (95% ) 99.5 % () MTBE (Methyl Tertiary Butyl Ether) 113 [1]

E10, E20, E60 E70 95 4 4 () Rotax 912S 2 100 1,352 [2] 1

1 Rotax 912S 100

2.

Rotax Rotax 912S 2 100 ( 2)

( 3) Star Gas 898

( Lambda) Techno Test 495/01 ( 4)

2 Rotax 912S

3

Rotax 912S

1 22 55

4

3. 95 95

E20 (.) E60 E70 95 (.) 95 60 5 15 ( 5)

5 60

E85

2,000 / ( 2,000 / ) Rotax 912S E85 4.

95 ( 60 ) ( 15 ) 95 ( 6)

() 15 2 () Lambda Lambda ( 1,800 /) ( 5,800 /) 95 95 ( 95) () 95

60

56 1 22

6 15 ,

5.

5.1 7 E60 E70 5,800

(kg)

0

50

100

150

200

1500 2500 3500 4500 5500

RPM

(k

g)

95E10E20E60E70

7 (: E60 E70 5,800

/) 5.2 8

(L/MIN)

0

0.2

0.4

0.6

1500 2500 3500 4500 5500

RPM

(L/M

IN)

95E10E20E60E70

8 5.3 Lambda 9

95 ( Lambda>1) E70 Lambda 2 Lambda E20 1 Stoichiometric Level [3]

Lambda

0

0.5

1

1.5

2

2.5

1500 2500 3500 4500 5500

RPM

Lam

bda

95E10E20E60E70

9 Lambda

5.4 10 14 2,500 / CO (CO2 ) 2,500 / CO2 10 CO E60 E70

15

1 22 57

HC HC HC 95

CO(%Vol)

0

4

8

12

1500 2500 3500 4500 5500

RPM

(%

Vol

) 95E10E20E60E70

10 (CO)

CO2(%Vol)

0

5

10

15

20

1500 2500 3500 4500 5500

RPM

C

O2(%

Vol)

95E10E20E60E70

11 (CO2)

HC(ppm Vol)

0

200

400

600

800

1000

1500 2500 3500 4500 5500

RPM

H

C (p

pm V

ol)

95E10E20E60E70

12 (HC)

O2

O2

O2

O2(%Vol)

0

5

10

15

20

1500 2500 3500 4500 5500

RPM

O

2(%Vo

l) 95E10E20E60E70

13 (O2)

NOX 95 NOX 7.375 ppm

NOx(ppm Vol)

0

400

800

1200

1600

1500 2500 3500 4500 5500

RPM

N

Ox (

ppm

Vol

)

95E10E20E60E70

14 (NOx)

5.5 m-1 15 95

58 1 22

0.57

0.110.16

0.020.09

0.0

0.2

0.4

0.6

(m-1

)

95 E10 E20 E60 E70

15 : EEC (European

Economic Community) m-1

6.

E60 E70 5,550 5,400 / ( 5,800 / take-off) (Fuel Heating Value) ( 14.7:1) ( Lambda )

( Lambda 1) [4]

E60 E70 CO HC 95 NOX NOX Catalytic

Converter CO2 CO CO2 CO 3,500 / O2 Lambda CO2 () O2 ( CO2 ) O2

(SI Engine) () 0.19 m-1

E10 E20

E60 E70 [1] Chan-Wei Wua, Rong-Horng Chenb, Jen-YungPu a, Ta-Hui Lina. The influence of airfuel ratio on engine performance and pollutant emission of an SI engine using ethanolgasoline-blended fuels. Atmospheric Environment 38 (2004) 70937100. [2] www.zenithair.com [3] Wei-Dong Hsieha, Rong-Hong Chenb, Tsung-Lin Wub, Ta-Hui Lina. Engine performance and pollutant emission of an SI engine using ethanolgasoline blended fuels. Atmospheric Environment 36 (2002) 403410. [4] Damon Bresenham, John Reisel and Ken Neusen, Spindt Air-Fuel Ratio Method Generalization for Oxygenated Fuels, SAE TECHNICAL PAPER SERIES, September 14-16, 1998

AEC011

1 22 59

Electrostatic precipitator for collection of particles from rubber wood combustion

1 1 2

1 . . 90112 0-7428-7036 0-7421-2893 [email protected] [email protected]

2 . . 90112 0-7428-8029-30 0-7421-2801 [email protected]

Chayasak Rattanachot1 Perapong Tekasakul1 Yutthana Tirawanichakul2 1Department of Mechanical Engineering, Faculty of Engineering, Prince of Songkla University, Hat Yai, Songkhla 90112

Tel: 0-7428-7036 Fax: 0-7421-2893 E-mail: [email protected] [email protected] 2Department of Physics, Faculty of Science, Prince of Songkla University, Hat Yai, Songkhla 90112

Tel 0-7428-8029-30 Fax 0-7421-2801 E-mail: [email protected] - 0.5 1 0.5 m 10 12 1 1 mm - 12 kV (DC) 58.43 % Abstract A wire-plate electrostatic precipitators (ESP) was constructed to test an efficiency in collecting smoke particles from wood burning. A 0.5x1x0.5 m ESP contained 10 collecting plates and 12 1-mm electrode wires per row between plates. Maximum input voltage was 12 kV (DC)

menett22 vol 1 (aec drc)

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