Mohd Nor Fakhzan Mohd Kazim
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Mohd Nor Fakhzan Mohd Kazim
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Mohd Nor Fakhzan , Mohd Kazim
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Mohd Kazim, M. N. F.
Mohd Kaz, Mohd Nor Fakhzan
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Scopus Author ID
55891362300
Researcher ID
FDP-7092-2022

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Investigation of vortex-induced vibration with different width of two bluff bodies in tandem arrangement for energy harvesting system

2021-05-24 , Aziz N.A. , Mohd Nor Fakhzan Mohd Kazim , Nasrul Amri Mohd Amin , Mohd Shukry Abdul Majid , Mohd Afendi Rojan , Nasir N.F.M.

Due to imperative of enhancement on Vortex-induced vibration (VIV) energy harvesting as renewable energy sources, dual bluff bodies which are triangle and cylinder in tandem arrangement with different width from each other are studied in terms of total deformation, directional deformation and voltage generated in order to determine the better bluff bodies for the piezoelectric film. This is due to the unsymmetrical wakes pattern, low frequency vortices, and low energy output produced by the system. The length and height of the bluff bodies were fixed to 0.1m and airflow used for simulations was 1.46m/s. The spacing ratio was calculated from 1 to 6 to examine various width between two bluff bodies that will affect the formation of the vortex at the downstream area. From the results, it can be concluded that triangle bluff bodies in tandem arrangement 0.6m from each other have resulted in the highest total deformation and effective voltage generated of 0.47mm, and 3.05mV, respectively. These data indicated the highest ability of energy harnessing. Furthermore, this model results in a consistent flagging direction of the piezoelectric that implying a good energy harvesting system.

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Comparison of Algebraic Reconstruction Technique Methods and Generative Adversarial Network in Image Reconstruction of Magnetic Induction Tomography (MIT)

2021-11-25 , Lubis A.J. , Nashrul Fazli Mohd Nasir , Zulkarnay Zakaria , Muzammil Jusoh , Azizan M.M. , Mohd Zakimi Zakaria , Mohd Nor Fakhzan Mohd Kazim , Rahman S.

Magnetic induction tomography (MIT) is a technique used for imaging electromagnetic properties of objects using eddy current effects. The non-linear characteristics had led to more difficulties with its solution especially in dealing with low conductivity imaging materials such as biological tissues. Two methods that could be applied for MIT image processing which is the Generative Adversarial Network (GAN) and the Algebraic Reconstruction Technique (ART). ART is widely used in the industry due to its ability to improve the quality of the reconstructed image at a high scanning speed. GAN is an intelligent method which would be able to carry out the training process. In the GAN method, the MIT principle is used to find the optimum global conductivity distribution and it is described as a training process and later, reconstructed by a generator. The output is an approximate reconstruction of the distribution's internal conductivity image. Then, the results were compared with the previous traditional algorithm, namely the regularization algorithm of BPNN and Tikhonov Regularization method. It turned out that GAN had able to adjust the non-linear relationship between input and output. GAN was also able to solve non-linear problems that cannot be solved in the previous traditional algorithms, namely Back Propagation Neural Network (BPNN) and Tikhonov Regularization method. There are several other intelligent algorithms such as CNN (Convolution Neural Network) and K-NN (K-Nearest Neighbor), but such algorithms have not been able to produce the expected image quality. Thus, further study is still needed for the improvement of the image quality. The expected result in this study is the comparison of these two techniques, namely ART and GAN to get the best results on the image reconstruction using MIT. Thus, it is shown that GAN is a better candidate for this purpose.

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