Aytaç Moralar

In today’s industry, due to the importance placed on occupational health and safety, regulations are being implemented to reduce noise in factory conditions. This study aims to reduce fan noise levels while simultaneously enhancing fan efficiency. We focused specifically on the evaporator fans used in the ammonia refrigeration tunnels at Unilever’s Algida ice cream production facility. Both physical and computational models of the fan blades were developed using Fluent and Phoenics computational fluid dynamics (CFD) software. Vibration analyses of the fan blades were performed using the modal analysis module. Through the analysis of pressure distributions on the existing fan blades, it was found that aerodynamic irregularities were the primary contributors to the noise. To address this, the NACA 6412 airfoil model was selected for the redesign, resulting in balanced pressure distribution across the blade surfaces and a reduction in noise levels from 96 dB to 78 dB.

Petroleum drilling sludge (PDS) is one of the most significant waste products generated during drilling activities worldwide. The disposal of this waste must be carried out using the most cost-effective methods available. The objective of this manuscript is to mathematically model the parameters of drying processes experimentally applied to PDS. For this purpose, this study employed two different artificial intelligence techniques: artificial neural networks (ANNs) and adaptive neuro-fuzzy inference systems (ANFISs). These methods were used to predict the parameters. In the calculations, the inputs included petroleum drilling mud with varying quantities (50 g, 100 g, and 150 g) and drying times, using a 120 W microwave drying power. The results indicated that the coefficient of determination (R²) and the root mean square error (RMSE) obtained during the test phase for ANFIS were 0.999965 and 0.005425, respectively, while for ANN, the R² and RMSE were 0.999973 and 0.004774, respectively. Analysis of the evaluation results revealed that both methods provided predictions for moisture content that were closer to experimental values compared to drying rate values.

Drying and storing food products have been widely used techniques for extending shelf life for many years. In recent times, there has been a focus on the drying of food residues, similar to the preservation of foods by drying. The process of drying a product involves reducing the moisture content within the product. However, the devices established to reduce moisture content are often costly and rely heavily on experience-based systems for determining the drying ratio. Therefore, in recent years, there has been significant interest in the mathematical modeling of drying processes and the creation of a model for system behavior using artificial intelligence methods. This study aims to model the drying process of hazelnut shells using artificial intelligence techniques, specifically artificial neural networks and fuzzy logic methods. The proximity of the models created to the experimental results of the drying ratio is examined.

Tr en Bu çalışmada mikrodalga konveyör kurutucu kullanarak kabak dilimlerinin kuruma davranışı araştırılmıştır. Kuruma deneyleri 5 mm, 10 mm ve 15 mm dilim kalınlıklarında, 1,5 kW ve 2,1 kW güçlerinde gerçekleştirildi. Elde edilen sonuçlara göre konveyör hızının azalması ile enerji tüketimi ve kuruma zamanı azalmıştır. Enerji tüketimi 2,014-3,520 kWh arasında ölçülmüştür. Kabak dilimlerinin istatiksel olarak kuruma davranışı beş deneysel model ile tanımlanmıştır. Tüm kuruma deney sonuçlarına göre Page model daha iyi sonuç vermiştir. Non-lineer regression analizi ile modeldeki katsayılar ve difüzyon katsayısı belirlendi. Difüzyon katsayıları 1,682x10^-7- 2,690x10^-6 m²/s arasında hesaplandı. Mikrodalga kurutucunun kabağın renk kalitesindeki etkisi göre en yüksek L* değeri 5 mm dilim kalınlığında, 2,1 kW ve 0,210 m/dk konveyör hızında belirlenmiştir. In this research work, drying characteristics of zucchini slices were investigated using a microwave conveyor dryer. The drying experiments with 5 mm, 10 mm, 15 mm thickness were carried out at 1.5 kW and 2.1 kW. The results showed that energy consumption and drying time decreased considerably with decreasing conveyor speed. Energy consumption was measured between 2.014-3.520 kWh. Particularly five empirical models were determined in defining the microwave drying behavior of zucchini slices by statistical analysis. The Page Model gave a better result for all drying experiments. The coefficients of the models were determined by non-linear regression analysis and the diffusion coefficient was calculated. The diffusion coefficients were found between 1.682x10^-7- 2.690x10^-6 m²/s. A color analysis was carried out to investigate the effects of microwave dryer on zucchini color quality. L* values at 2.1 kW and 0.210 m/min dried samples with 5 mm thickness were determined as the highest value.

Elektrik ve güneş enerjisi ile çalışan taşıtlar hareket enerjilerini elektrik motorları aracılığı ile almaktadır. Bu motorlara enerji ise bataryalar tarafından sağlanmaktadır. Elektrikli araçların batarya durumu, sıcaklığı ve anlık hızı gibi veriler kalan yol miktarı gibi bilgilerin hesaplanması için oldukça önemlidir. Bu çalışmada bu verilerin ölçülmesi ve uzaktan takip edilebilmesi için fiziksel programlama platformları kullanılarak bir telemetri sistemi geliştirilmiştir. Veriler çeşitli sensörler aracılığı ile ölçülmüş, fiziksel programlama platformu aracılığı ile yorumlanmış ve GSM şebekesi aracılığı ile internet üzerinden bir sunucuya gönderilip, geliştirilen bir web sitesi üzerinde yayınlanmıştır.

Bu çalışmada 5mm dilimindeki patatesin mikrodalga bantlı kurutucuda mikrodalga gücünün (1500W ve 2100W) ve bant hızının (0,175, 0,210 ve 0,245 m/dak) kurutma zamanı, renk değişimi ve enerji tüketimine etkisi araştırıldı. Elde edilen sonuçlara göre mikrodalga gücünün artması ve bant hızının azalması ile enerji tüketimi azalmıştır. Dokuz adet kurutma modelinin uygunluğunu belirlemek için deneysel ve teorik nem oranları dikkate alınarak korelasyon katsayısı (r), standart hata (e_s) ve (χ²) hesaplandı. Tüm kurutma şartları için Page modelin en uygun model olduğu belirlenmiştir. Efektif difüzyon katsayısı 2,958.10^-7 ve 3,587.10^-6 m²/s aralığında hesaplanmıştır. Kurutma süresince en az enerji 0,175m/dak ve 2100W gücünde belirlenmiştir.