IJET Vol. 10, Issue 1, March 2025
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Öğe A MIMO Antenna Utilizing Modified Apollonian Fractal for Sub-6 5G Wireless Applications(İstanbul Gelişim Üniversitesi Yayınları / Istanbul Gelisim University Press, 2025) Yussuf, Abubeker A.; Paker, SelçukIn this paper, a quad-element multiple-input multiple-output (MIMO) antenna is designed using a modified Apollonian fractal shape for 5G Wireless communication. The proposed antenna comprises four radiating Apollonian fractal elements placed at optimal positions, along with a bottom layer incorporating a segmented ground plane. Each radiating element is composed of a microstrip feed with a quarter-wave transformer to improve impedance matching. The proposed Apollonian fractal-shaped MIMO antenna operates over the frequency range of 3.3–3.8 GHz, achieving an impedance bandwidth where S11 is less than -10 dB and mutual coupling below -20 dB. The envelope correlation coefficient (ECC) remains below 0.05, ensuring excellent diversity performance. Furthermore, the performance parameters of the Apollonian fractal- shaped MIMO antenna are evaluated based on S-parameters, such as the envelope correlation coefficient and channel capacity. Experimental measurements show that the ECC is lower than 0.05, while the channel capacity loss is below 0.6, reflecting reasonable agreement with the simulation results.Öğe An Overview of ANN based MPPT and an Example(İstanbul Gelişim Üniversitesi Yayınları / Istanbul Gelisim University Press, 2025) Rezaee, Mehdi; Şahin, Yusuf GürcanThe study presents an overview and a simulation of maximum power point tracking (MPPT) for Photovoltaic (PV) systems that uses an artificial neural network (ANN) controller as proof of concept. Solar energy must be harvested with high efficiency as the world turns to renewables. The usual Perturb and Observe (P&O) and Incremental (InC) method loses power by oscillating around the Maximum Power Point (MPP) and reacts slowly to sudden weather changes. The work therefore tests an ANN as a better choice. The authors survey earlier ANN MPPT studies that cover many network types, training schemes and mixed strategies. They then build a MATLAB/Simulink model that runs an ANN controller and a P&O controller on the same PV array. The ANN learns from Istanbul 2020 weather data. The results show the ANN reaches 252 W and 87.9% of efficiency while P&O reaches 241 W and 84.26% of efficiency, and InC reaches 245 W and 78.1% of efficiency. The ANN also tracks the MPP faster and with steadier behaviour when irradiance varies. These outcomes confirm that ANN MPPT can raise the energy output of PV systemsÖğe Optimization of Fixed Supported Castellated Steel Beams(İstanbul Gelişim Üniversitesi Yayınları / Istanbul Gelisim University Press, 2025) Albayati, Marwan Abdulkareem Shakir; Noori, Ahmad Reshad; Kayabekir, Aylin EceCastellated beams have garnered increasing attention in various fields due to their aesthetically appealing design, diverse geometric shapes, environmental friendliness, and economic advantages in terms of time, cost, and performance. These beams particularly excel in resisting bending without increasing their weight. The novelty of this paper, is to optimize the performance of castellated beams by maximum vertical deflection, represented as the objective function. This is achieved by determining the optimal dimensions of the cross-section using three optimization algorithms: Gray Wolf Optimization (GWO), Particle Swarm Optimization (PSO), and Differential Evolution (DE). This study focuses on three different types of material for castellated beams: S235, S255, and S355. The results revealed that the PSO and DE algorithms produce very similar outcomes, while the GWO algorithm shows slightly different results. Overall, all three algorithms demonstrate good capability in engineering applications, with a slight preference for the PSO and DE algorithms.
