Sürdürülebilir Kalkınma Amaçları

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• MakaleAçık Erişim2026Scopus SJRQ1/r/munzur/752
  Numerical analysis of PCM integrated in solar dryers for thermal efficiency

  Bakır Gür, Eda; Işık, Erdem; Uçar, Aynur

  Solar dryers using phase change materials buffer heat, yet the combined influence of airflow regime and PCM placement on melting remains underexplored. A controlled like-for-like study fixed geometry and PCM properties while varying placement and operating conditions. A 3D transient CFD model simulated a forced-convection dryer with RT28HC over Re = 3000–9000 and inlet temperatures Ti = 50–60 °C. Raising either Re or Ti shortened melt time, and three-wall coverage melted faster and more uniformly than a rear-wall-only layout. For three walls, melt time dropped from 13 h (50 °C, Re = 3000) to 7 h (60 °C, Re = 9000) (−46 %) for the rear wall it fell from 19 h to 11 h (−42 %). A 10 °C increase in Ti reduced overall melt time by 4 h across Re. Practically, three wall PCM with Re ≥ 6000 at Ti = 60 °C achieved reliably 7–9 h melting, enabling late afternoon heat release without auxiliary heating.

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  AtıfScopus17·WoS16·OpenAlex12

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• MakaleAçık Erişim2025Scopus SJRQ1/r/munzur/1097
  Deep learning and optimization-based feature selection for fetal health classification using CTG data

  Kaya, Turgay; Kaya, Duygu; Atar, Fatmanur

  This study introduces a DL and metaheuristic optimization-based framework for fetal health assessment using cardiotocography (CTG) signals to mitigate maternal and neonatal mortality. One-dimensional CTG signals were transformed into 2D representations, and deep feature extraction was performed using AlexNet. Feature vectors FC6, FC7, and their combination were subjected to optimization via Whale Optimization Algorithm (WOA + DL) and War Strategy Optimization (WSO + DL), utilizing updated fitness functions tailored for feature selection. Experimental results with SVM classifiers demonstrated superior performance with FC6 (89.98 %) and WSO + DL (90.17 %). FC6 exhibited strong discriminative capacity, while FC7 contained semantically richer features. The concatenated FC6 + FC7 vector increased feature diversity. WSO + DL achieved optimal balance across classification accuracy, feature subset size, convergence rate, and overall performance metrics. The integration of DL and metaheuristic algorithms effectively isolated informative feature subsets, improving training efficiency, minimizing redundant/noisy data, reducing overfitting risk, and enhancing classification accuracy. Optimization method selection proved critical to overall model performance.

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  AtıfScopus6·WoS1·OpenAlex6

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• MakaleAçık Erişim2021Scopus SJRQ1/r/munzur/3046
  Control of switched reluctance generator in wind power system application for variable speeds

  Omaç, Zeki; Cevahir, Ceren

  Switched reluctance generators (SRGs) come into prominence in other electrical machines with its simple structure, only stator winding, reliability, high fault tolerance and the possibility of working within wide speed range. These generators are used especially in wind power plants due to their ability to operate in variable speed range and applications of aviation and electric cars. In this study, the control of the SRG was performed. A simulation of SRG driver in Matlab/Simulink was performed and the real-time implementation control of SRG is carried out on DS1103 Ace kit digital signal processor to determine the performance of the SRG. The output voltage of the SRG is controlled by the proportional-integral (PI) voltage controller. As a result, the graphs of change in SRG phases currents and SRG output voltage were obtained according to different parameters. Simulation results compared with experimental results. Consequently, they overlap on experimental results.

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  AtıfScopus25·WoS8·OpenAlex27

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