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1. Effect of Temperature on Diffusivity of Monoethanolamine (MEA) on Absorption Process for CO2 Capture

E. E. Masiren, N. Harun, W. H. W. Ibrahim; F. Adam 1

2. Design of Selectable Modems for MC-CDMA Based on Software Defined Radio Ali Kareem Naha and Yusnita Rahayu 7

3. Simulation and Fabrication of Open-Type Boiler of Fish Cracker Production Line Mohd Zaidi Sidek, Mohd Syahidan Kamarudin, Mohamad Nafis Jamaluddin 15

4. Photocatalytic conversion of CO2 into methanol: Significant enhancement of the methanol yield over Bi2S3/CdS photocatalyst M. Rahim Uddin, Maksudur R. Khan, M. Wasikur Rahman, Abu Yousuf, Chin Kui Cheng 23

5. A New Neuron Ion Channel Model with Noisy Input Current Ahmed Mahmood Khudhur, Ahmed N Abdalla 29

6. An Analysis of Beliefs among UMP International Students towards English Oral Presentation “Pilot Study”

Abdelmadjid Benraghda, Zuraina Binti Ali, Noor Raha Mohd Radzuan. 36

7. Computational Fluid Dynamics study of Heat transfer enhancement in a circular tube using nanofluid.

Abdolbaqi Mohammed Khdher, Wan Azmi Wan Hamzah, Rizalman Mamat 40

8. Development of Solar Oven Incorporating Thermal Energy Storage Application Roziah Binti Zailan, Amir Bin Abdul Razak, Firdaus Bin Mohamad 47

9. Examination of selected Synthesis parameters for composite adhesive-type Urea-Formaldehyde/activated carbon adhesives

Tanveer Ahmed Khan, Arun Gupta , S. S. Jamari, Rajan Jose 52

10. Maximum system loadability based on optimal multi facts location Maher A. Kadim and Yahya N. Abdalla 59

11. The effect of filler ER4043 and ER5356 on weld metal structure of 6061 aluminium alloy by Metal Inert Gas (MIG) Mahadzir Ishak, Nur Fakhriah Mohd Noordin, Ahmad Syazwan Kamil Razali

, Luqman Hakim

Ahmad Shah 66

12. Effect of strong base during co-digestion of petrochemical wastewater and cow

dung

Md. Nurul Islam SIddique and A.W. Zularisam 74

http://www.sciencedirect.com/science/article/pii/S0016236113011526http://www.sciencedirect.com/science/article/pii/S0016236113011526

INTERNATIONAL JOURNAL OF ENGINEERING TECHNOLOGY AND SCIENCES (IJETS) Vol.3 (1) June 2015

Effect of Temperature on Diffusivity of Monoethanolamine (MEA) on

Absorption Process for CO2 Capture

E. E. Masiren

Faculty of Chemical and Natural Resources Engineering,

Universiti Malaysia Pahang

Lebuhraya Tun Razak, 26300 Gambang, Kuantan, Pahang,

Malaysia

W. H. W. Ibrahim Faculty of Chemical and Natural Resources Engineering,



Malaysia

N. Harun Faculty of Chemical and Natural Resources Engineering,



Malaysia

[email protected]

F. Adam Faculty of Chemical and Natural Resources Engineering,



Malaysia

Abstract— Diffusion coefficient study gains an

interest to know the mass transfer properties of

molecules especially in study of the absorption process.

The main objective of this study is to investigate the

effect of temperature on diffusivity of MEA absorption

process for CO2 capture. Three different values of

process temperature were chosen for simulation in this

study, 25oC, 40oC and 45oC. The MD simulation was

carried out at NVE (200ps) and NPT (1ns) ensemble in

Material Studio 7.0 software. Mean Square

Displacement (MSD) analysis was done to compute the

self-diffusion coefficient of molecules in tertiary system

(MEA+H2O+CO2). The results show that the rate of the

diffusion coefficient is increased as temperature

increased. Diffusion coefficient at 45oC is the highest

compared to others temperature. MD simulation is used

to study details about absorption process and capture

CO2 acid gases. The simulation diffusivity result

obtained from this work shows higher compared with

theoretical results.

Index Terms— Molecular Dynamic, Simulation,

Amine Absorption Process, Monoethanolamine,

Carbon Dioxide, Mean Square Displacement

I. INTRODUCTION

Recently, the increment of CO2 composition in air will be contributing the increment of the global

temperature. IPCC (Intergovernmental Panel on

Climate Change) is an international agency, whose

plays a role in preparing a report about the global

climate change [1]. IPCC is one of agencies in this

world which extensively conduct the research to

overcome the global climate change problem. At

present, there are many CO2 capturing chemical

materials are known such as amine-solvent, organic

molecular cages, ionic liquids, metal-organic

framework, zeolite and carbon-materials [2]. In this

study, amine-solvent is used to determine the

diffusivity of CO2 in amine-based absorption

process. Absorption process is a process in the

scope of post-combustion capture process. This

technology has been established over the year since

1930’s [3]. MEA, monoethanolamine (C2H7NO) is

a primary amine. Which has been used as solvent in

CO2 capture due to higher performance in the

absorption process [4].

Molecular Dynamic (MD) simulation was run on

molecules species to calculate the diffusion

coefficient. This computational method has become

an effective tool to explore more deeply about

absorption process and also CO2 capture. MD

simulation used to study the molecular properties

such as the diffusion coefficient [5]. This

computation technique can also study others

thermodynamic condition at atomic level that

cannot be study by doing experimental. Moreover,

this technique has many advantages compare to

chemical experimental study such as environmental

friendly and money saving [6]. In CO2 capture cost

process, more than half is distributed to the

absorbent regeneration part [7]. Study on the

thermodynamic properties is essential before

operating the absorption process in pilot plant. In

addition, cost for experimental research to study the

diffusion coefficient is high particularly at

operating condition of higher pressure and

temperature [8]. Besides that, the equipment used

for study diffusion coefficient of solute in liquid

solvent in low concentration is expensive. MD

simulation also is an option to study the diffusion

coefficient of solute in supercritical fluid because

it’s difficult to run by experimental [9]. Therefore,

the computation measurement study offers better

approach to do the research on diffusivity.


Factors that affected the diffusion are concentration

gradient, pressure gradient and temperature

gradient [10]. Diffusion coefficient, density and

viscosity are used to calculate the mass transport

properties of molecule in a system [11]. Diffusion

coefficient is usually seen as DAB in equation which

represent as the flux of a diffusing component A

and B with unit m2/s. In MD simulation, mean

square displacement (MSD) analysis or the mean

square of the distance molecule move is used

calculate the rate of diffusion coefficient. The

theories which can be used to study MSD analysis

are the Fick’s laws, Einstein-Smoluchowski theory

[5], [12] and the Maxwell-Stefan theory [13]. In

MD simulation, the Maxwell-Stefan theory will be

used in MSD analysis. This theoretical can be used

to calculate the diffusion of mixture system [14].

Besides MSD analysis, velocity auto-correlation

function analysis also used to study transport

diffusion system [12].

The literature study on diffusion coefficient by

using MD simulation is very limited in open

literature. Result diffusion coefficients of MEA,

CO2 and H2O in various systems were reported in

the literature such as study diffusion coefficient of

H2, H2O and CO in various n-alkanes by using MD

simulation [15], calculate diffusion coefficient of

pure water by MD simulation [16], calculate

diffusion coefficient of MEA, DEA, MDEA and

DIPA [17] by experimental, calculate diffusion

coefficient of PZ and MDEA by Tylor dispersion

method experiment [18].

The temperature and pressure as operating

conditions in actual absorption process in pilot

plant are in ranges 38oC-60

oC and 1 bar,

respectively [19]. The aim of this paper is to

discuss the effect of temperature on diffusivity of

CO2 and MEA in MEA solution during absorption

process.

II. . SIMULATION METHODOLOGY

MD simulation was done by using software of

Material Studio (version 7.0) which installed on HP

Z420 workstation. This software is licensed

software manufacture by Acceryls (San Diego,

USA) [20]. The MD simulation was started with

replicate the structure of single molecule. The

structure of molecules is obtained from Royal

Society of Chemistry database [21]. There are three

phases in running MD simulation which are the

relaxing phase, the equilibrium phase and the

sampling phase [5]. Geometry optimization step

were carried out on each of the molecules to ensure

the stable molecular geometry to be used in further

simulation steps. The default algorithm used is the

Smart Algorithm and Fine convergence level. The

simulation boxes are developed using the

amorphous cell calculation model in Material

Studio software. Type of forcefield used is

COMPASS and summation method used is Ewald

to calculate electrostatic energy or electrical

interaction [22]. Once the simulation box is

developed, this model is simulated for box energy

minimization. The simulation is started with

equilibration of the system under constant number

moles, volume and energy (NVE) ensemble for 200

ps with random initial velocities. The simulation

process is continued in dynamic mode under

constant number of moles, pressure and

temperature (NPT), isothermal-isobaric ensemble

for 1ns. Within this time step, the integration of

equation algorithm is going through. The time step

choose to be used is 1 fs. 1 fs time step is reported

to enough for ensure the molecules in amorphous

cell box does not overlapping [22]. Pressure is kept

constant at 1 atm to achieve an equilibrium density.

The simulation box consists of 300 molecules of

MEA, 300 molecules of CO2 and 1000 molecules

of H2O. Fig 1 shows the molecular structure of

molecules CO2, H2O and MEA. Table 1 shows the

simulation parameters to represent MEA absorption

process. This study is an the extension of previous

study [23]. This model is simulated at three

different temperature, 25oC, 40

oC and 45

oC.

(a)

(b)

(c)

Fig. 1: Schematic labelling of molecules (a),

Monoethanolamine (b) Water (c) Carbon

Dioxide

The Einstein relation is used to calculate MSD in

MD simulation. Equation 1 shows equation to

determine coefficient of molecular diffusion, D in

MD simulation [13]. The slope of MSD graph is


diffusion coefficient value, D. The value have

divide with 6 as the system is in 3-dimensional

system and do conversional unit (Å2/ps to m

2/s) as

shown in equation 1.

Di,self =1

6Nilimm.δt

1

m.δt∑ < (rl,i(t + m. δt) −

Nil=1

rl,i(t) >2 (1)

Ni = the number of the molecules of component i

δt = the time step used in the simulation m = the total number of the time steps

rl,i(t) = the position of the lth molecule of component I at time t

The Stokes-Einstein relation also can be used in

calculation of MSD. Equation 2 shows the Einstein

equation over the time interval [24]:

6Dt =< |r(t) − r(0)|2 >= 𝑀𝑆𝐷(𝑡) (2) Where r(t) = [x(t), y(t), z(t)] show the coordinates atoms at time t. Equation 3 is used to

calculate the diffusion coefficient as a function of

MSD results [25].

D =1

6

d

dtMSD(t) = constant (3)

III. RESULT AND DISCUSSION

MD simulation is used to calculate CO2 and MEA

diffusivity in MEA solution [13]. MEA is classified

as bases with the presence of nitrogen atom which

has unshared electron pair. It is consists of

hydroxyl group which help for the solubility in

water and amino group is used to assist the

alkalinity in water to absorb the acid gas [26].

Table 2 shows the diffusion result in simulation. As

shown in table 2, as temperature increased, the

value of diffusion coefficient also increased.

Molecule is colliding with each other in periodic

boundary result the repeat motion which called as

diffusion. When give a heat, the atom will be

vibrational motion and collide with other neighbour

atom [27].Moreover, increasing in temperature

condition will be affect the rate constant of reaction

[28]. The diffusion coefficient of CO2 is higher

than MEA and H2O as depicted in Table 2. The

molecular mass of MEA, CO2 and H2O are 61, 44

and 18, respectively. As the molecular mass (size

of the molecule) increase, the diffusion rate will be

slower.

In this simulation, MEA solution is selected as

chemical solvent were used to absorb CO2 gas. CO2

gas will diffuse from gas to liquid phase then

dissolve in liquid phase to do interaction and

reaction [29].

Table 2: Diffusion result for simulation

Simulation

Components/ Temperature 45oC 40

oC 25

oC

CO2 (m²/s) 9.0897E-09 8.6780E-09 7.2200E-09

H2O (m²/s) 6.6975E-09 6.6600E-09 5.8200E-09

MEA (m²/s) 5.2770E-09 5.3830E-09 4.6400E-09

Fig 2 to 4 shows the plot of the MSD versus time at

temperature 45oC, 40

oC and 25

oC, respectively.

These graph used to calculate diffusion coefficient

have a straight line with a constant slope. The slope

was the MSD value increase linearly with time.

From these graphs, can be seen that the slope were

increased with the increased of temperature. The

results obtain from this work show some different

with the theoretical calculation.

Fig. 2: Prediction of diffusion coefficient graph for MEA, H2O and CO2 at 45

oC



oC


oC

COMPARE WITH MATHEMATICAL EQUATION

In order to validate the accuracy of simulation

result, theoretical calculation is done. Two type of

theoretical calculation is used which are Wilke-

Chang equation [30] and based on Versteeg and

van Swaaij (1988) study [17]. Versteeg and van

Swaaij (1988) study is used because related to CO2

diffusion in amine solution.

Theoretical calculation of diffusivities in liquids

(Wilke-Chang equation)

The Wilke-Chang equation is used to calculate the

diffusivity of MEA and H2O [30]. Equation 4

shows the Wilke-Chang equation.

𝐷𝐴𝐵 = 1.173 × 10−16(∅𝑀𝐴)

1/2𝑇

𝜇𝐵𝑉𝐴0.6 (4)

MA = the molecular weight of solvent B

𝜇𝐵 = the viscosity of B VA = the solute molar volume at the boiling point

= the association parameter for solvent, 2.6 for

water

T = the temperature of system

Theoretical calculation of diffusion CO2 in MEA

aqueous from Versteeg and van Swaaij (1988)

The diffusion of CO2 in MEA aqueous can be

calculate by using the N2O analogy in literature

[17] [31]. Equations 5 to 9 are shows the way how

CO2 diffusivity calculated on aqueous MEA amine.

𝐷𝐶𝑂2 = 𝐷𝑁2𝑂 (𝐷𝐶𝑂2𝐷𝑁2𝑂

) 𝑖𝑛 𝑤𝑎𝑡𝑒𝑟 (5)

𝐷𝐶𝑂2(𝑚2. 𝑠−1) = 2.35

× 10−6𝑒𝑥𝑝 {−2119

𝑇(𝐾)}

(6)

𝐷𝑁2𝑂(𝑚2. 𝑠−1) = 5.07

× 10−6𝑒𝑥𝑝 {−2371

𝑇(𝐾)}

(7)

𝐷𝑁2𝑂= (5.07 + 0.865𝐶𝑀𝐸𝐴 + 0.278𝐶𝑀𝐸𝐴

2 )

× 10−6exp (−2371 − 93.4𝐶𝑀𝐸𝐴

𝑇(𝐾))

(8)

𝐶𝑀𝐸𝐴 =10𝐶%𝑤/𝑤𝑑

𝑀𝑤 (9)

Table 3 shows the comparison of simulation results

with theoretical results. Based on this table, the

value of exponent (E-09) is same for all results. But


when compared to diffusivity value, the simulation

result is quite larger compared to theoretical results.

The simulation result obtained from this work

shows bigger than theoretical result. The reasons

are these two systems were different in number of

molecules, operating conditions and simulation

approximation (force field, summation method,

ensemble, algorithm etc.) as previous simulation

work. In this simulation work, it applied the

molecular mechanics principle. Its means, MD

simulation consider the physical interaction and

without chemical interaction such in quantum

mechanics and experimental study. Furthermore, a

reliable result of diffusion coefficient of solutes in

solution can be obtained if longer MD simulation

need to run expect up to 3 ns of NPT ensemble [5],

2 ns of NVT ensemble [22] and 30 ns of NVT

ensemble [15]. [25] Also literature shows the

calculation of diffusion coefficient by using

numerical computation need to run over a long time

periods and/or used large ensemble size for

statistical reasons. However, this present simulation

work only can be done NPT ensemble part until 1

ns due to limited time and lower performance of

computer processor used. Different type of

ensemble for production phase contribute to

different result of diffusion coefficient. [12], [22],

[9] proposed the simulation procedure by using the

canonical equilibrium ensemble (NVT) and [25]

used PVT ensemble (the temperature-pressure-

volume) in order to compute the diffusion

coefficient.

Table 3: Comparison simulation results with theoretical results

Simulation

Components/ Temperature 45oC 40

oC 25

oC

CO2 (m²/s) 9.0897E-09 8.6780E-09 7.2200E-09

H2O (m²/s) 6.6975E-09 6.6600E-09 5.8200E-09

MEA (m²/s) 5.2770E-09 5.3830E-09 4.6400E-09

Theoretical (used Wilke-Chang equation)

CO2 (m²/s) in water 3.3893E-09 3.1661E-09 1.1034E-09

H2O (m²/s) in water 5.1372E-09 4.7989E-09 3.3537E-09

MEA (m²/s) in water 1.9655E-09 1.8360E-09 1.2831E-09

Theoretical (used Versteeg and van Swaaij (1988))

CO2 (m²/s) in water 3.0001E-09 2.6972E-09 1.9183E-09

H2O (m²/s) in water 2.9303E-09 2.6013E-09 1.7766E-09

MEA (m²/s) in aqueous MEA 2.2954E-09 2.0577E-09 1.4467E-09

CO2 (m²/s) in aqueous MEA 2.4002E-09 2.1181E-09 1.4214E-09

IV. CONCLUSIONS

Mean square displacement calculation is used to

calculate the diffusivity of molecules in MEA

solution. The rate of the diffusion coefficient is

increased as temperature increased. Rate of

diffusion coefficient at 45oC is the highest

compared to 40 o

C and 25 o

C. The diffusion

coefficient of CO2 is larger than H2O and MEA in

liquid state due to small molecular weight. Even

though the values of diffusion coefficient of this

simulation work are higher than experimental and

theoretical data, the trend follows the theoretical

with CO2 has the highest diffusion coefficient.

While, it is good effort to study the diffusion

coefficient by MD simulation. The main reason of

different diffusivity value is probably due to MD

simulation used molecular mechanic principle that

may ignore some factors for cheaper calculation.

MD simulation basically involved the physical

interaction and based on molecular mechanic

principle. Besides that, this simulation is run in

condition of 1 ns NPT ensemble and on lower

performance of computer processor. Further study

need to carry out in order to study deeply about

CO2 absorption in MEA solution.

V. ACKNOWLEDGMENTS

The author would like to give appreciation to

University Malaysia Pahang and the Accelrys Asia

Pacific for fully cooperate to complete this work. In

addition, for financial support from the Higher

Education Ministry of Malaysia through

fundamental research grant scheme (FRGS) on

RDU130109.

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Design of Selectable Modems for MC-CDMA Based on Software

Defined Radio

Ali Kareem Nahar a,b

a Faculty of Electrical and Electronic

Engineering, University Malaysia Pahang ,

26600Pekan, Pahang, Malaysia

Yusnita Rahayu a

b Universities of Technology, Department of

Electrical Engineering, Baghdad, Iraq

MC-CDMA technique is the combination of

Orthogonal Frequency Division Multiplexing (OFDM)

technique and Code Division Multiple Access (CDMA)

technique and collects the benefits of both techniques to

provide higher data rates and greater flexibility for

voice, data, video and internet services for future

wireless systems. In this paper MC-CDMA system based

on Software Defined Radio (SDR) was proposed. The

proposed data spread model consists of gold code and

Selectable six modulation types (BPSK, QPSK, 8QAM,

16QAM, 32QAM and 64QAM). In addition, OFDM is

designed by both FFT and IFFT for detecting ideal

channel. The programming is done by using MATLAB-

Simulink tool as well as M-files presented for each

modem. Matlab 13A. The transmitter send 4, 3 and 2 bit

to the receiver in which the system indicate is too big

for 4 and 3 bit therefore the transmitted but reduced to

two bit for successfully system work. To achieve

optimum encoding and decoding signal the all

modulation techniques use 5 MHz to 20 MHz spectrum

frequency. Moreover the bandpass signal generation

has optimal utilized area to satisfy the required

sampling rate

I. INTRODUCTION

Recently, the growth of video, voice and data communication, the users demanded high date rate

over the Internet wireless environment where the

spectral resource is scarce. To fulfill the

requirements SDR-CDMA is very efficient way to

overcome inter-symbol interference (ISI) on

frequency selective channels [1].

Many research focus on OFDM scheme which has

severed disadvantages such as nonlinear

amplification, sensitivity to frequency offset and

difficulty in subcarrier synchronization [2]. MC-

CDMA is a combination of CDMA and OFDM and

has the benefits of both systems [4, 5]. Thus, the

parameters of OFDM become the basic parameters

of MC-CDMA. In [3,4] proposed OFDM based on

wavelet, where both FFT and IFFT blocks are

replaced by an inverse discrete wavelet transform

(IDWT) and discrete wavelet transform

(DWT)respectively. In [5,6] propose MC-CDMA

system based on a combination of OFDM and

CDMA system for better robustness against

multipath, interference rejection, and impulse noise

frequency reuse, etc. In [7] proposed OFDM for

broad-band local area wireless based on standards

IEEE802.11a [8, 9].

In this paper focus inn analyze the parameters of

OFDM selectable modulation in MC-CDMA. The

simulation parameters considered are: guard time

interval, sampling rate, symbol duration, and

number of data subcarriers. The analysis carried out

using MATLAB. The OFDM and MC-CDMA

analyze under different parameters to determine the

better of the two for the modern wireless

communications.

II. RELATED WORK

In the recent past, a number of study projects in the

field of SDR networking have been presented. In

[10] proposed a new design of CDMA digital

transmitter for a multi-standard SDR base band

stage. The platform involves of reconfigurable and

reprogrammable hardware platform which provide

different standards with a common platform, and

implemented with FPGA by create VHDL model

of CDMA transmitter. In [11] introduce a basic

acquisition system for finding and classifying Base

Stations (BSs) in visibility in the framework of a

CDMA wireless positioning system, based on IS-

95 cellular standard. In [12], concentration on the

importance of MC-CDMA and use adaptive

modulation, the exploitation of fluctuations channel

quality, so that they can exchange more traffic

multimedia using the same bandwidth, a high

efficiency in bandwidth and diversity inherent to

the channel fading as compared with OFDM and

DS-CDMA in the Fig. 1 shown

Fig. 1 MC-CDMA and DS-CDMA use the whole

bandwidth

Each of these blocks was tested using FPGA

advantages 7.2 software during design process; the

same process was done at the receiver part where

using each of the modules was experienced during

design process [13]. Moreover, Mahbub, [14]


proposed an implementation of DS-CDMA

transmitter. In [15] was a show implementation

topic of a digital transmitter for an OFDM through

adjusted VHDL in contradiction of system

generator results. Canet’s work is absorbed on

solutions for the OFDM signal generation in IF and

base-band. Implementation of SDR implies more

specific design and analysis procedures than the

implementation of conventional transceiver

systems. Selection of hardware components for

transceiver implementation, that follows the SDR

concept, is the first and crucial step necessary for

its implementation. All selected hardware

components together form a hardware platform for

SDR creation. During the process of forming a

hardware platform it is necessary to achieve a

compromise between desired, scalability,

flexibility, modularity and performance of the SDR

system [16]. Scalability is related to modularity,

and it allows the system to be enhanced to improve

capability such as increasing number of channels

that a base station could handle. In addition,

flexibility is the capability of a system to switch

variety of air-interfaces and protocols, even if they

have yet to be defined. Also, modularity of a

system allows easy replacement or progress of sub-

systems to take advantage of new technologies

[16]. In [17], that they discussed the M-QAM for

forward link of MC-CDMA schemes with

interference dissolution to support high data rate

service, and provided an analytical BER

performance of the system. In [18], emphasizes the

suitability of high level design tools when

designing sophisticated systems, and the

importance to design FPGA systems rather than

ASIC for accomplishing one day the SDR idea and

give a high level overview of the FPGA

implementation, that work emphasizes the packet

detection, synchronization, preamble correlator,

channel estimation and equalization; that is

primarily at the OFDM receiver for the

IEEE802.11. In [19], developed a SDR networking

is platform using GNU Radio and the USRP. They

integrated a Tun/Tap device into their solution and

additionally studied the impact of channel quality

and different modulation schemes. In [20], based

on their previous observations, MacKenzie et al.

developed a split functionality approach in order to

overcome the communication delays introduced

through SDR and the USRP. Moving time sensitive

functionality closer to the radio promises better

performance in terms of delay. The drawback,

however, is the decreased flexibility and higher

implementation complexity.

III. THE PROPOSED SYSTEM

The general layout for proposed system is shown in

Fig. 2. The main parts and functions of the

implemented proposed system are:

1. Transmitter: The transmitter is responsible for

generating the symbols of the transmitted data

which is transmitted over a wireless channel. Six

modems are used in this transmitter, these are

BPSK, QPSK, 8QAM, 16QAM, 32QAM and

64QAM that can be select which type of these

modems above is turned on and the others are

turned off by the response of the selectable modem

unit.

2. Receiver: This is responsible for data reception

and demodulation of the received data. The

selectable modem unit is used in the receiver

section to decide which demodulation and decision

circuit are used to demodulate the received

modulated signal and received the data signal.

Fig.2. Proposed system layout


Fig. 3 describes the design and implementation

procedure used for the proposed SDR system. The

SDR parameters are set up according to

IEEE802.16e CDMA standard. Then, the design is

implemented as a model using MATLAB

(combination MATLAB-Simulink and M-file) and

functional simulation is performed to performance

evaluation.

Fig. 3 The proposed SDR system implemented in MATLAB

IV. RESULT AND DISCUSSION

The system parameters setting includes specifying

the different types of modulation/demodulation and

other related system operations that the SDR could

handle [21]. Table 1. shows the proposed design

system parameters. The SDR system is very

flexible and can change its parameters easily.

The variation of the BER are performed according

to the variation ratio for energy of data bit to the

power spectrum density (Eb/ No). Fig. 4 shows the

performance of modulation over channel. Table 2.

shows the representation of data which is greatly

generated. Fig. 5 represents I and Q-symbol which

is multiplied by PN-I and PN-Q respectively. Fig. 6

represents the I and Q signals with 64-QAM

modulation transmitted in MC-CDMA.

The variation of the BER are performed according

to the variation ratio for energy of data bit to the

power spectrum density (Eb/ No). Fig. 4 shows the

performance of modulation over channel. Table 2.

shows the representation of data which is greatly

generated. Fig. 5 represents I and Q-symbol which

is multiplied by PN-I and PN-Q respectively. Fig. 6

represents the I and Q signals with 64-QAM

modulation transmitted in MC-CDMA. The

performance of system using 64-QAM modulation

system will be evaluated by plotting the BER

versus the (Eb/No) in the presence of channel for

different values of Doppler frequency. Fig. 7 shows

the effect of AWGN over 64- QAM modulation,

fig. 8 shows the effect of channel on the system.

Table. 1: Design system parameters

paramter Selected types or values explain

Modlation type BASK,QPSK,8QAM,16Q

AM,32QAM,64QAM

BPSK, QASK and M-QAM

used in this system to increase

data rate of transmitssion

IF frequency 5-20MHz Moderate frequency can be used

to implement SDR system

Sampling frequency 100MHz This value is selected for better

simulation results

FFT size 256

8-inputs and the values of the

twiddle factor, each equation

as paths even and odd

Sprading cods Gold code 1.2288Mp/s


Fig. 4 Performance of different modulation schemes

Table. 2 Representation of 32-QAM, 16-QAM, 8QAM, QPSK andBPSK signals

symbo

l

32QAM 16QAM 8QAM QPSK BPSK

I-

Channe

l

Q-

Channe

l

I-

Channe

l

Q-

Channe

l

I-

Channe

l

Q-

Channe

l

I-

Channe

l

Q-

Channe

l

I-

Channe

l

Q-

Channe

l

0 -3 5 -3 3 -3 1 1 1 1 0

1 -1 5 -3 1 -3 -1 -1 1 -1 0

2 -1 -5 -3 -1 -1 1 -1 -1

3 -3 5 -3 -3 -1 -1 1 -1

4 -5 3 -1 3 1 1

5 -5 1 -1 1 1 -1

6 -5 -1 -1 -1 3 1

7 -5 -3 -1 -3 3 -1

8 -3 3 1 3

9 -3 1 1 1

10 -3 -1 1 -1

11 -3 -3 1 -3

12 -1 3 3 3

13 -1 1 3 1

14 -1 -1 3 -1

15 -1 -3 3 -3

16 1 3

17 1 1

18 1 -1

19 1 -3

20 3 3

21 3 1

22 3 -1


23 3 -3

24 5 3

25 5 1

26 5 -1

27 5 -3

28 3 5

29 1 5

30 1 -5

31 3 -5

Fig. 5 I and Q-symbol multiplied by PN-I and PN-Q with 64QAM

Fig. 6 MC-CDMA using 64-QAM transmitted signal.


Fig. 7 Simulation results of MC-CDMA by using 64-QAM modulation

Fig. 8 Simulation results of MC-CDMA by using 64-QAM modulation

V. CONCLUSIONS

In this paper, selectable six models were proposed

to enhance the performance of OFDM scheme.

Performance of proposed MC-CDMA systems

enhanced with increasing processing gain, but with

large processing gain the performane of systems

degraded. Multimode soft decision circuit to

determine the regions of the received signal

acceptable to define the final output data. The

decision circuit includes 8, 16, 32 and 64 regions.

Division of input data by the variable factor

according to number of bit per symbol. The

variable factor is 2,3,4,5 and 6 and is determined by

selectable circuits. Generation of bandpass signal

for six modems in order to set the IF signal

required by SDR systems, as well as the generation

of the bandpass signal which has optimal utilized

area with satisfied the required sampling rate. SDR

will have a key role to play, in the cognitive

systems. We have suggested the SDR algorithms

for successful data transmission in bandwidth

obtainable. The performance of proposed MC-

CDMA schemes enhanced through increasing

processing gain, but with large processing gain the

performance of systems degraded.

References

1. Kumar SS, Sukanesh R. Performance Analysis of Multi-Carrier Code Division

Multiple Access System Under Clipping

Noise. European Journal of Scientific

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York, November 1999.

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Transmission Scenarios. ICITA

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House, London, 2000.

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AMC and MCCDMA for Mobile

Environments. International Journal of

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CDMA Technique in FPGA Using

Verilog HDL. International Conference

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Engineering, 2011.

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Speed Multi-code CDMA. IEEE

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Science Issues March 2012; 9(2): 612-

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Networking, Wireless and Mobile

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Simulation and Fabrication of Open-Type Boiler of Fish Cracker

Production Line

Mohd Zaidi Sidek

Faculty of Manufacturing Engineering,

Universiti Malaysia Pahang, 26600 Pekan,

Pahang [email protected],

Mohd Syahidan Kamarudin



Pahang

[email protected],

Mohamad Nafis Jamaluddin



Pahang [email protected]

Boiling process is performed at the final stage in fish

cracker processing and it is a longest process. It creates

a bottleneck and limits the daily production of fish

cracker. Traditionally, fire woods are used to heat the

boiler. The invention of diesel-fired boiler has improved

the process but there are still some issues at the station.

Therefore, a new boiler is designed to improve the

boiling process by using LPG burner which has 2.9 %

higher calorific value than diesel. The boiler designed

was simulated to study the heat convection inside the

boiler by using SolidWorks Flow Simulation to analyze

the temperature distribution inside the new boiler.

Multiple layers bottom plate of the boiler consist of an

aluminium plate sandwiched between two stainless steel

plates is used to increase the rate of heat transfer from

the flame into the water inside the boiler. The result

from the simulation proves that the multiple layers

bottom plate of the boiler has a higher rate of heat

transfer than the single layer plate where the time taken

for water to boil is 42.2% shorter than the single

stainless steel layer bottom plate boiler.

I. INTRODUCTION

Fish cracker is one of the famous and highly relished snack foods in Malaysia and it is

originated from east coast of peninsular Malaysia

[1]. It is well known and highly demanded due to

its crispy on the outside but tender on the inside if

it is fried. Besides, fish cracker can be eat by just

boil it which gives fishier flavour according to

some people. Both fried and boiled fish cracker is

best to be eaten with special fish cracker chilli

sauce. The main ingredient of fish cracker is fish,

sago flour, salt and water. The high requirement of

fish cracker in the market urge entrepreneurs to

increase their production but they face a lot of

problem to fulfil the market demand. In the

production of fish cracker, most manufacturers are

still using traditional manufacturing practices with

low competitiveness and poor efficiency which

limit the daily production of the fish cracker. As a

result, these manufacturers cannot meet the demand

of the customer. Thus, there is a necessity to

employ a standard processing procedure in order to

keep the quality while meeting the high production

to provide the consumer demands of the delicious

fish cracker. There are several stages of processing

that are needed to be taken to make fish cracker as

shown in Figure 1.

Fig. 1.Process sequence in fish cracker

manufacturing

Previously, fish cracker manufacturers carry out the

processes manually such as the process to roll the

dough into huge sausage-like fish cracker and

mailto:[email protected]:[email protected]


shaping square fish cracker is still being done

manually. In addition, the process to boil the fish

cracker is done traditionally by boiling water from

burning firewood. This method is not very efficient

where it is difficult to control the fire and it also

produces smoke and soot to the surroundings.

Therefore, at that moment, the manufacturers

cannot produce high production of fish cracker to

meet the market demand.

Nowadays, Small and Medium Industry (SMI)

sector has improved very well in the term of their

manufacturing method. The technology that is used

in other food processing industry such as nugget,

burger and meat ball has influenced many local

foods including fish cracker to be commercialized

[2]. The fish cracker manufacturers have improve

their processes hence increase the production of

fish cracker by the use of automated machines to

perform a certain task such as the processes to

mince and mixing the kneaded fish meat. Other

than that, automatic diesel fire-tube burner is

installed to the boiler to perform the task boiling of

fish cracker. Automated processes can help fish

cracker manufacturers to increase the production to

meet the market demand.

Fish cracker industry has caught the eye of the

Malaysian government therefore it is included into

East Coast Economic Region (ECER) as the east

coast of peninsular Malaysia is rich in resources

and the raw material for fish product food. The fish

industry is put under food and halal product

initiatives.

Traditionally, the process of boiling fish cracker is

by burning firewood. This method is not suitable as

it is hard to control the fire, efficiency is low where

a lot of firewood is used and the burning of

firewood produces smoke and soot on the

surrounding. Currently, the invention of fire tube

burner by using diesel fuel has improved the

boiling process. This burner does not need a worker

to control the fire as the diesel injection is

automatically control via temperature sensor that

sense the temperature of the water inside the tank.

Furthermore, the smoke from burning diesel is

channelled away from the working area. This is a

lot better than the previous one as the water boils

faster by using this method.

Apart from that, the burner still has few things to

be improved because the uneven temperature

distribution as the temperature of water near the

diesel burner is high but it decrease as it moves far

from the burner. The result of this problem is the

fish cracker that are put on the side near the burner

cook faster than the fish cracker that are placed

further from the burner which lead to the bottleneck

on the production.

The aims for this study are to design a new boiler

and to simulate the heat convection inside the new

boiler by using SolidworksFlow Simulation.

II. LITERATURE REVIEW

A. Fish Cracker Industry

Malaysia is unique country of different cultures

that has led to in varieties of foods. It is important

that these traditional foods are preserved for future

generations. By using modern technologies and

traditional techniques, manufacturers could

produce more hygienic way of processing and

preserving food [3]. Thus, there is an urgent need

to refine the processing of traditional foods in

response to new societal needs. Refining and

sustaining traditional foods are essential in facing

the forces of globalization [4].

In the production of fish cracker, most producers

are still using traditional manufacturing practices

with low competitiveness and poor efficiency.

Therefore, there is a need to employ a standard

processing procedure in order to maintain the

quality while meeting consumer demands for

safety, quality and nutritional value of these foods.

Traditionally, fish cracker is precooked by boiling

in water. Study by Bakar (1983) reviewed the

boiling and steaming methods in processing fish

cracker. The researcher found that steaming of fish

cracker does not prove to be feasible and the study

suggested several modifications in the processing

steps in fish cracker preparation are essential. On

the other hand, [1] reviewed in terms of sustaining

and promoting of this local food, more publicity

should be performed continuously and producers of

fish cracker must achieve consistent quality and

safety as it represents Malaysia’s identity.

Traditional fish cracker production methods result

in products of poor quality, with uneven expansion

characteristics, dark objectionable colours and

varying shapes, sizes and thicknesses as well as

low hygiene [6]. Siaw, Idrus, & Yu (2007) have

attempted to upgrade product quality. They have

introduced mechanization and standardization into

fish cracker making. Their process is less time

consuming and gives a better-quality product

compared to the traditionally produced fish cracker.

The two essential ingredients in fish cracker

making are starch and fish. Fish such as ‘Ikan

Parang’ (Chirocentrus dorab), ‘Ikan Tamban

beluru’ (Clupea leiogaster) and ‘Ikan Selayang’

(Decapterus macrosoma) are preferred although

other fishes are also used for making fish cracker.

Tapioca or sago starch is used but sago starch is

said to give the best product in terms of texture and

flavor [8]. Fish cracker can be eaten as soon as it is

boiled and together with chili sauce.

B. Bottleneck In Fish Cracker Processing

The purpose of boiling fish cracker is to precook

for further processing although it is palatable with

chili sauce for some people. According to [5], only

15 minutes of boiling required to achieve complete

cooking of fish cracker while 3 hours is needed to


achieve the same result by steaming. Processing

conditions such as boiling of product can reduce

microbial levels, although recontamination takes

place during post- processing and handling of food

[9].

C. Boiler Specifications

There are several factors that must be studied

before designing a boiler such as material, heating

configuration, temperature distribution and heat

transfer rate [10]. Designing a boiler without a

proper research on the topic will lead to a failure

and will waste lots of money if the design is

fabricated. Therefore, appropriate study on the

boiler specifications should be done before

designing it to ensure the new boiler will produce

good heating characteristics and improved the

production in the boiling station in fish cracker

processing.

Temperature distribution plays an important role

for a boiler in the boiling station as it will affect the

cooking time for the fish cracker [11]. Uneven

temperature distribution will lead to bottleneck

where 10 to 15 minutes are taken to check whether

all fish cracker are properly cooked. Therefore, the

shape and the geometry of the boiler must be able

to allow even temperature distribution inside the

boiler. It is very crucial for the boiler to have the

characteristic because it will solve the problem of

different cooking time of the fish cracker.

Another important factor in boiler specifications is

the material selection for the boiler. Different

material has their own characteristics such as

mechanical properties, thermal properties,

corrosion resistance and durability. Important

aspect such as hygiene is vital in fish cracker

processing as poor hygiene may lead to health

illness such as food poisoning to the consumers.

The contamination of surfaces by spoilage and

pathogenic micro-organisms is a cause of concern

in the food industry. One of the decisive arguments

when choosing materials for processing line

equipment, along with their mechanical and

anticorrosive properties, has become hygienic

status (low soiling level and high cleanability). Of

these materials, stainless steel, which is widely

used for constructing food process equipment, has

previously been demonstrated to be highly hygienic

[12]. However, stainless steel can be produced in

various grades and finishes, affecting bacterial

adhesion because of their various topographies and

physic-chemical properties [13]. The main

difference between commercially available grades

is their relative composition in iron, chromium and

nickel. Austenitic stainless steels containing

chromium and nickel, such as AISI 304, are widely

used in the food industry because of their high

resistance to corrosion by food products and

detergents.

Other elements may be added to improve

anticorrosive properties, such as molybdenum in

AISI 316, often used in dairies. Other materials

such as ferritic stainless steel are used in various

applications because of how easily they can be

formed and welded (catering). Moreover, one grade

can be obtained in more or less rough finishes such

as pickling finish (2B) and bright annealed (2R),

depending on their final steel making process [14].

Higher heat conductivity of the cooper used as

heating plate can result in short recovery time [15].

Currently, the invention of fire tube burner by

using diesel fuel has improved the boiling process.

This burner does not need a worker to control the

fire as the diesel injection is automatically control

via temperature sensor that sense the temperature

of the water inside the tank. Apart from that, the

burner still has few things to be improved because

the uneven temperature distribution. The result of

this problem is the fish cracker that are put on the

side near the burner cook faster than the fish

cracker that are placed further from the burner

which lead to the bottleneck on the production.

In addition to the burner, it also has a blower to

circulate the heat along with vents that remove the

by-products of combustion and allow fresh air to

flow into the burner for a steady burn rate. One of

the most important aspects in making a good

heating system is the design of the heating system

and its tank. Therefore, factors such as better

temperature distribution and control, faster

cooking, less energy, safer operation, better

sanitation and flexibility must be taken into account

in considering the design. Plus, the shape of the

heating unit is also an important design

consideration. Ekundayo (1994) stated that the

optimum configuration to achieve the most steady-

state rate of convection was with the heating

element placed in the lower half of the tank.

Research Methodology

In this analysis, the current boiler design and

application are recorded to be analysed. Then, a

new design fish cracker boiler created to overcome

the issues of the current boiler.

The design of the new fish cracker boiler is based

on several considerations and factors which will be

explained next section. The drawing of the new

boiler is as shown in Figure 2.

To verify the simulations, an experimental test

method is used to examine if a correlation between

the test method and the simulations exist. The aim

is to find a parameter that can be evaluated in the

simulation. In the experiment, a Liquefied

Petroleum Gas (LPG) burner is use to heat 1.15 L

of water in a pot until the point of boiling as shown


in Figure 3. The same parameters from the

experiment will be used in the simulation and the

result of the simulation is compared with the

experimental result to see whether the simulation is

valid or not.

With the validated simulation, the design of the

new boiler can be simulated to analyse the heat

convection characteristics inside the new boiler by

using the similar method that is used in the

simulation validation in order to determine whether

the new design is capable to solve the problem of

bottleneck hence increase the production of fish

cracker in the factory.

Fig. 2. Design of fish cracker boiler

Fig. 3.Experiment apparatus

III. RESULT AND DISCUSSION

A. . Boiler Design

There are several considerations that must be

included in designing the new boiler .The

temperature distribution and material selection in

fabricating the boiler were the main issues to be

concerned and as an innovation of the boiler

design, an insulation system of the boiler was

created.

To avoid the uneven distribution ot the

temperature, a centred-stove boiler concept was

selected with a big cylindrical shape replacing the

u-shape heating system. The current u-shape, the

water boils faster on the nearest side to the blower

and vice versa on the side further from the blower.

Figure 4 shows the drawing of the tank that is used

to boil fish cracker at the factory. The fire from

diesel burning flows inside the hollow tube inside

the tank which heat is transferred to the water. To

prove that the temperatures are varies inside the

tank; thermocouples are used to measure the water

temperature at point A, point B and point C. The

temperature is measured and the graph of the

temperature at the points is shown in Figure 5.

Fig. 4. Tank drawing

Fig. 5. Temperature distribution in tank

4.2. Simulation Validation

For the validation purpose of the simulations, an

experimental test method is used to examine if a

correlation between the test method and the

simulations exist. The aim is to find a parameter

that can be evaluated in the simulation. In the

experiment, an LPG burner is used to heat 1.15 L

of water in a pot until the point of boiling. The

same parameters from the experiment will be used

in the simulation and the result of the simulation is

compared with the experimental method. The

measured temperature of the flame from LPG

burning in the experiment is 820 °C. This

parameter will be used at the bottom plate of the

pot in the simulation validation as wall temperature

boundary condition as shown in the Figure 6.

Graph in the Figure 6 shows the water temperature

(°C) versus time (minutes) for the experiment. The

temperature steadily increased from 27.32 °C until

maintained at 84.97 °C after 7.23 minutes of heat

applied.


Fig. 6. Measured flame temperature

Fig. 7. Experimental result

Figure 8 shows the graph of temperature over time

for the simulation on the pot. The graph is

automatically plotted by Flow Simulation software.

The temperature of water increased steadily from

26.72 °C until maintain at 87.74 °C after 6.33

minutes.

From both graphs, we can see that the temperature

of water for both experiment increased steadily

until maintain at temperature around 84 °C to 87 °C

after 820 °C of flame temperature is applied at the

bottom surface of the pot. The simulation takes

shorter time which is 6.33 minutes while the

experiment takes 7.23 minutes. This is due to the

ideal condition in the simulation such as the purity

of water in the simulation differs slightly with the

water that is used in the simulation. Plus, the flame

temperature in the simulation is maintained at 820

°C from the first second until the end of the

simulation. Meanwhile, the flame temperature in

the experiment takes a few seconds to reach 820

°C. Therefore, the slight variation in both result can

be tolerate thus validate the simulation that is done

in SolidWorks Flow Simulation software and the

same simulation can be applied at the new boiler to

simulate the finite volume analysis to study the heat

convection at the inside of the boiler.

Fig. 8. Simulation result graph

4.3. Simulation Result

4.3.1. Result of Multiple Layer Bottom Plate Boiler

The result of the finite volume simulation on the

new boiler is illustrated in the Figure 9 which show

the temperature contour cut plot from the front

plane of the boiler. This cut plot is the temperature

distribution inside the boiler after 15.83 minutes of

heating. From the cut plot contour, temperature

distribution inside the boiler range from 97.36 °C

to 100.16 °C.

Fig. 9. Temperature contour cut plot

Fig. 10.Flow trajectory of water inside the boiler

The new boiler has a better temperature distribution

which may improve the boiling process of fish

cracker and increase the productivity. The time

taken to ensure all fish cracker is fully cooked after

15 minutes can be reduced as all fish cracker inside

the boiler are cooked at temperature range from

97.36 °C to 100.16 °C. Even temperature

distribution is achieved in this boiler because of the

shape of this boiler and the heat is applied at the

bottom part of the boiler which makes the water to

circulate to all part inside the boiler.

From the flow trajectory of the water inside the

boiler, the circulation of water can be determined

as shown in the Figure 10. The circulation is due

the buoyancy effect inside the boiler where hotter

water moves upwards due to lower density and vice

versa for cooler water. Although the temperature of


water is just slightly varied, the difference in

density will determined the movement of the water

which creates the flow inside the boiler. The line

with arrows in the Figure 10 shows the direction of

the water flow. In the middle part of the boiler have

hotter water flowing upward. As it reaches the top

surface, the temperature of the water will drop a

little and move downward by the side part of the

boiler and the cooler water will be heated again as

it reaches the bottom part where the heat is applied.

This result proves the finding by Jullien, Bénézech,

Carpentier, Lebret, & Faille, (2003) that is the

optimum configuration to achieve the most steady-

state rate of convection was with the heating

element placed in the lower half of the tank.

B. Comparison of Single Layer Plate and Multiple Layer Plate

Figure 11 shows the temperature over time of

boiling process that is simulated on the boiler with

multiple layers bottom plate. The time taken for the

water to reach 100 °C is 15.3 minutes.

The graph in Figure 12 shows the temperature over

time of boiling process that is simulated on the

boiler with single layer bottom plate. The time

taken for the water to reach 100 °C is 26.47

minutes.

From the graphs shown in Figure 11 and Figure 12,

the boiler with multiple layers bottom plate will

boils the water faster than the boiler with single

layer bottom plate. This proves that the multiple

layer bottom plate has a higher rate of heat transfer

which transfers the heat faster from the LPG flame

into the water through the multiple layers bottom

plate.

𝑃𝑒𝑟𝑐𝑒𝑛𝑡𝑎𝑔𝑒

=Single layer time − Multiple layer time

𝑆𝑖𝑛𝑔𝑙𝑒 𝑙𝑎𝑦𝑒𝑟 𝑡𝑖𝑚𝑒 𝑋 100%

𝑃𝑒𝑟𝑐𝑒𝑛𝑡𝑎𝑔𝑒 = 42.2% The new boiler with multiple layer bottom plates

has higher rate of heat transfer by 42.2 % compared

to single layer bottom plate. Thus, the multiple

layer bottom plate is capable able to increase the

daily rate of fish cracker production.

Fig. 11. Multiple plies plate graph

Fig. 12. Single ply plate graph

IV. CONCLUSION

New boiler design can improved the heating rate

and temperature distribution of water inside the

boiler thus improving the boiling process of fish

cracker where the time taken to ensure that all fish

cracker is fully cooked can be reduced thus solving

the bottleneck problem which is due to 10 to 15

minutes taken to check for all fish cracker to fully

cook. All fish cracker that are boil inside this boiler

will take 15 minutes to fully cooked as the

temperature is even distributed inside this boiler

which is around 97.36 °C to 100.16 °C.

Multiple layers bottom plate is better than single

layer because it has 42.2 % higher rate of heat

transfer by single layer bottom plate boiler as the

multiple layers configuration reduced the total

thermal resistance. The layer of aluminium in

between two stainless steel layer has improved the

rate of heat transfer. This layer configuration is

preferable to be used since the stainless steel has

low conductivity but the boiler must be made of

corrosion resistance material and provide good

hygiene.


V. RECOMMENDATION FOR FUTURE RESEARCH

Based on the findings of the present investigation,

the following recommendations are made for

further research:

The further improvement for the new boiler can be

made to increase the performance of the boiler such

by using higher thermal conductivity material to

replace the aluminium with copper that has 401

W/mK which is almost twice as large as the value

of thermal conductivity of aluminium. The study on

the boiler with copper plate in between stainless

steel at the bottom plate can be done by using the

same method used in this simulation.

The system to control the LPG burner can be

developed to save the fuel consumption at the

boiling station in keropok ikan industry. This

system also will eliminate the need of worker to

monitor the LPG flame. Furthermore, this system

will also reduce the fuel cost for boiling fish

cracker.

ii. Samples with fiber volumetric ratios of 1.5

kg.m-3 indicated better corrosion resistance

compared to the other samples.

iii. In this research, using coral aggregate for

producing concrete samples showed that this

concrete composition was not a practical

composition. Corrosion rate in this concrete was at

least twice that was shown in siliceous concrete.

iv. The results show that 6 mm length fibers were

not the suitable size to be used in concrete. The

result of using fibers with length of 12 and 19 mm

was approximately the same, with the optimum size

being 12 mm.

v. Apart from increasing corrosion resistance, the

presence of polypropylene fibers decreased the

permeability, volumetric expansion and contraction

of concrete, which in turn had reduced the chance

of concrete cracking.

VI. ACKNOWLEDGMENTS

This research was made possible with a scholarship

from Ministry of Highr Education, Malaysia and

support from University Malaysia Pahang (UMP).

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Photocatalytic conversion of CO2 into methanol: Significant

enhancement of the methanol yield over Bi2S3/CdS photocatalyst

M. Rahim Uddin, Maksudur R. Khan*, M.

Wasikur Rahman, Chin Kui Cheng

Faculty of Chemical and Natural Resources

Engineering, Universiti Malaysia Pahang,

26300 Gambang, Pahang, Malaysia [email protected]

Abu Yousuf

Faculty of Engineering Technology, Universiti

Malaysia Pahang, 26300 Gambang, Pahang,

Malaysia

ABSTRACT The present work is a significant approach

to explore the photo-conversion of carbon dioxide

(CO2) into methanol on Bi2S3/CdS photocatalyst under

visible light irradiation. In this perspective, Bi2S3

nanoparticles have been successfully synthesized via

corresponding salt and thiourea assisted sol–gel

method. An innovative hetero-system Bi2S3/CdS has

been proposed to achieve methanol photo evolution and

its photocatalytic activities have been investigated. The

photocatalysts are characterized by X-ray diffraction

(XRD), ultraviolet-visible spectroscopy (UV-Vis)

instruments. Results show that the photoactivity and

visible light response of commercial CdS loaded Bi2S3

is higher than that of synthesized CdS. The

photocatalytic activity of Bi2S3/CdS photocatalyst was

enhanced and the highest yield of methanol was 590

μmol/g when the weight proportion of Bi2S3 to CdS

was (2:1).

Key Words : CO2 reduction Photocatalyst,Bi2S3/CdS,

Visible light; Methanol

I. INTRODUCTION

The continuous increase in atmospheric CO2 leads to climate change, which is one of the major threats

of times. The rapid consumption of fuel resources

and the undergoing concerns over the emissions of

CO2 have stimulated research objectives on the

conversion of CO2. It is urgent to reduce the

accumulation of CO2 in the atmosphere. There are

three effective ways to reduce CO2 emissions:

reducing the amount of the produced CO2, using

CO2 and storing CO2, where transformation of CO2

into chemicals is an attractive option and fulfils the

recycle use of CO2 [1, 2]. Photocatalytic process

for CO2 reduction provides a suitable approach for

clean and environmental friendly production of

hydrocarbon by visible light. However, in order to

harness sunlight to produce hydrocarbons from

CO2 conversion, there are different fundamental

requirements that must be satisfied [3-8]. Firstly,

light must be efficiently absorbed to generate

electron-hole pairs for the electron transfer from

one conduction band to other. Secondly, either the

recombination of the photo-generated electron-hole

pairs like to be prevented for the CO2 adsorption on

catalyst surface. Thirdly, undesirable reactions or

products, such as photocorrosion or degradation of

the photocatalyst, as well as environmental

unfriendly products, must be prohibited by

adjusting the pH before suspending the catalyst onto

reaction medium. To develop suitable

photocatalysts, these fundamental key factors and

the aims of photocatalytic reduction of CO2 need to

be satisfied [3, 9-11].

As for photocatalytic conversion of CO2 to

methanol, CdS is the most popular photocatalyst

due to its excellent stability, innocuity and low

price. In addition, due to its larger surface and

regular structure has also been brought to much

attention in the field of photocatalytic conversion

of CO2 [12, 13]. The band-gaps of CdS and Bi2S3

were narrower and their conduction bands were

more negative than those of other photocatalysts

[12, 13], t

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