Tan Wee Choon
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Tan Wee Choon
Official Name
Tan, Wee Choon
Alternative Name
Choon, Tan Wee
Tan, W. C.
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Scopus Author ID
54891879100

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MICROWAVE ABSORPTION ANALYSIS ON HEATED EDIBLE SPIRULINA WITH VARIOUS TEMPERATURES

2023-05-01 , Cheng Ee Meng , Tan Wei Hong , Tan Wee Choon , Lim Eng Aik

This paper discusses the microwave absorption analysis of edible Spirulina by using WR62 and WR90 rectangular waveguides in conjunction with Agilent P-series Vector Network Analyzer (PNA). Heat might lead to the degradation of spirulina. This phenomenon involves the chemical and physical reaction that is associated with the variation of dielectric properties. These properties determine the propagation mechanism of microwaves within the sample or material. Hence, an assessment method to detect a nutrient change in spirulina due to heat is necessary. In this context, a microwave absorption measurement system was developed to study the reflection coefficient, transmission coefficient, and absorption coefficient of Spirulina tablets over temperature. The transmission/Reflection line method is well-known because it is non-destructive and rapid in analyzing chemical and physical properties. In this work, Spirulina tablet is used since it is a popular food supplement that is believed to be able to treat diseases is and good for health. The reflection, transmission, and absorption measurements were conducted on Spirulina from 12.4GHz to 18GHz.

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Improved K-Means Clustering for Initial Center Selection in Training Radial Basis Function Networks

2022-01-01 , Lim Eng Aik , Tan Wee Choon , Tan Wei Hong , Cheng Ee Meng

Radial Basis Function networks accuracies mainly affected by its center selection from dataset. K-means (KM) clustering is a widely in numerous field for data classification and centers selection. However, initial centers selection poses high impact on KM clustering outcome. It suffers from its immense reliance on the initial centers selection algorithm from the dataset. KM algorithm has been enhanced for its performance from diverse perspectives over the years. Nonetheless, a good balance between quality and efficiency of the centers selected by the algorithm is not attained. To overcome this issue, this paper proposed an improvement on KM clustering algorithm in getting initial centers and reduce its sensitivity to initial centers. This paper introduce the use of improved K-means (KM) clustering that consider the each point distance as probability for selecting the initial centers with radial basis function network (RBFN) training algorithm. The proposed approach uses improved KM for centers selection in RBFN training algorithm shows accuracy improvement in predictions and with simpler network architecture compared to the conventional RBFN. The proposed network called IKM-RBFN was tested against the conventional RBFN, KM-RBFN, back-propagation neural network and long short-term memory neural network in FOREX EURUSD pair price predictions. The results are compared to proposed method on its root mean square error (RMSE) and mean absolute error (MAE) results. The proposed method shows promising results in improving RMSE accuracy over 20% in compared to other tested networks.

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K-means Algorithm Based on Flower Pollination Algorithm and Calinski-Harabasz Index

2023-01-01 , Lim Eng Aik , Tan Wee Choon , Mohd Syafarudy Abu

Aiming at the problems that the Flower Pollination (FP) algorithm is easy to fall into the local optimum, the searchability is weak, and the k-means algorithm is easily affected by the selection of the initial clustering centre, a k-means algorithm based on the FP algorithm is proposed. Six benchmark functions test the improved FP algorithm. The effectiveness of the k-means algorithm based on the improved FP algorithm was tested and verified with UCI machine learning and artificial datasets. The verification results showed that the improved FP algorithm improved based on ensuring a faster convergence speed. Compared with other algorithms, the performance of this algorithm has been significantly improved in all aspects.

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Numerical analysis on the effect of diluted hydrogen fuel by a fixed amount of supplied hydrogen using a quasi-three-dimensional solid oxide fuel cell model

2023 , Tan Wee Choon , Lim Eng Aik , Cheng Ee Meng , Tan Wei Hong , Hamimah Abd Rahman

Solid oxide fuel cell (SOFC) has excellent fuel flexibility for various fuels. Despite some drawbacks like storage and transportation, hydrogen stands up as the best fuel for SOFC. Hydrogen fuel is diluted non-reactive gas species before it is supplied to the SOFC. In this study, a quasi-three-dimensional SOFC model with real microstructure is used to analyse the effect of the diluted fuel mixture. The hydrogen fuel is diluted with nitrogen and a small amount of steam. The mole amount of hydrogen within fuel mixtures is kept constant. On the other hand, the air that is supplied to the air channel of the SOFC remains unchanged. It is found that the cell that is supplied with the highest concentration of hydrogen has the highest performance due to its high partial pressure of hydrogen within the fuel mixture. Such a high partial pressure promotes a low anode concentration loss. Also, the cell that is supplied with a low hydrogen concentration is unable to benefit from its high average cell temperature as its performance is drained by the low partial pressure of hydrogen within the fuel mixture.

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Numerical analysis on the anode active thickness using quasi-three-dimensional solid oxide fuel cell model

2023 , Tan Wee Choon , Lim Eng Aik , Hamimah Abd Rahman , Abdullah Abdul Samat , Cheen Sean Oon

A quasi-three-dimensional solid oxide fuel cell (SOFC) model reduces the computational cost by strategically ignoring the thinnest direction in an SOFC by incorporating a charge-transfer current density model to represent its active thickness in electrodes to represent its complex phenomenon in an electrode. Therefore, high accuracy of this charge-transfer current density model is required. The concentration loss is mathematically related to the charge-transfer current density based on the dusty-gas model together with activation and ohmic losses in this work. The numerical results from this study are validated with the experimental results. The influence of anode's thickness towards anode active thickness is studied with the anode thickness of 5, 10, 50, 100, 500 and 1000 μm. It is found that the quasi-three-dimensional SOFC model is capable of analysing SOFC with a sufficiently thick electrode. Also, a thick electrode and a high average current density result in a thin active thickness.

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Numerical analysis of the effect of pore size toward the performance of solid oxide fuel cell

2022-01-01 , Tan Wee Choon , Lim Eng Aik , Cheng Ee Meng , Tan Wei Hong

The effect of the anode pore size is numerically investigated with the aids of artificial solid oxide fuel cell (SOFC) microstructure information. The standalone effect of the pore size is impossible to be realized by the experimental approach. Additionally, the complete real microstructure information is also limited in the open literature as it required sub-micron 3D imaging equipment. The dusty-gas model is implemented into the developed quasi-3D SOFC model for the gas diffusion in the anode. The model with real microstructure information is successfully validated. The actual anode pore radius of 0.283 Î¼m is artificially replaced with a radius of 0.025, 0.050, 0.250, 0.500, and 2.500 Î¼m. Decrement of area-specific reactant (ASR) for the anode concentration is found with the increment of pore radius. Also, such increment promotes a small increment of ASRs for the anode activation and the anode ohmic loss.

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Microwave Dielectric Properties and Absorption Analysis for Seashells Through Transmission-Reflection Method Using Waveguides

2022-01-01 , Cheng Ee Meng , Tan Wei Hong , Tan Wee Choon , Lim Eng Aik

This work is aim to investigate microwave dielectric behavior and microwave absorption of seashells through transmission-reflection method using waveguides. Microwave dielectric and absorption characteristic are judged through the measured reflection and transmission coefficient via two waveguides in conjunction with P-series network analyzer (PNA) from 8.2 GHz to 18 GHz. Anadara granosa seashells are collected in this work for comparison. The measurement was conducted in various temperature, i.e. 35 â„ƒ, 50 â„ƒ and 60 â„ƒ. The sample was prepared in specified dimension, according to the operating frequency range. Results in this study reveals absorption coefficient is function of frequency and dimension. As the frequency increase, the | S11 | decrease whereas the | S21 | increase. Better absorption was demonstrated by seashells in room temperature than the heated seashell.

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Acoustical simulation and analysis on the resonator muffler

2022-10-01 , Tan Wei Hong , Cheng Ee Meng , Lim Eng Aik , Tan Wee Choon , Amaresh S.G.

With the modernisation of transport during the period of industrial urbanization, vehicles on the road are increasing, and it brings noise disturbances caused by the internal combustion engine of vehicles. This study involves the acoustical model development and analysis of the vehicle muffler. In this study, the resonator type of muffler is considered, and the transmission loss (TL) is used as the parameter to evaluate the acoustic performance of the muffler. The muffler CAD model is created using Solid works, and the acoustical analysis is conducted using COMSOL Multiphysics. The developed muffler model is tuned several times to obtain the optimum TL. The study yielded a wide range of TL across a range of frequencies. It is found that constrictions to the intake and exhaust pipes generated a higher TL by ~20dB than the original dimensions. Using an acoustic dampener further increases the TL of the muffler with a maximum increase of 18%. The inclusion of an acoustic dampener paired with the reduced diameter of the intake and exhaust pipes resulted in the analytical model generating the highest TL in the resonator muffler.

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