ÖzBu çalışmada, Nisan 2017 -Mart 2018 tarihleri aralığında Mersin için ölçülen günlük toplam global güneş ışınım değerlerinin yapay sinir ağı kullanılarak modellenmesi yapılmıştır ve literatürde bulunan yaygın modellerin günlük toplam global güneş ışınım değerlerini tahmin etme performansları incelenmiştir. Günlük ortalama hava sıcaklığı, bağıl nem, rüzgar hızı, güneşlenme süresi ve bulut kapalılığı verileri, Devlet Meteoroloji İşleri Genel Müdürlüğü'nden temin edilmiş olup güneş ışınım değerleri ise piranometre ile ölçülmüştür. Sonuç olarak, incelenen modeller içerisinde en iyi tahmin performansını belirlilik katsayısı (R 2 ) 0,83 olan Model 37 (Zhang ve Huang) göstermiştir. AbstractIn this study, the daily total global solar radiation values measured for Mersin between April 2017 and March 2018 were modeled using artificial neural networks and the performance of estimating daily total global solar radiation values of the common models in the literature was investigated. Daily average air temperature, relative humidity, wind speed, sunshine duration, and cloud cover data are obtained from the Turkish State Meteorological Service and solar radiation values are measured with a pyranometer. As a result, Model 37 (Zhang and Huang) showed the best prediction performance among the models examined, with the coefficient of determination (R 2 ) being 0.83.

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In this study, applicability of wind and solar energy technologies in a non-residential building located in Mersin, Turkey is investigated. As the non-residential building, a polyclinic was examined. Meteorological data was obtained from Turkish State Meteorological Service to investigate the solar and wind energy technologies. The data was examined statistically. By using wind turbine with 0.9 kW rated power, 2223.5 kWh electricity energy was generated. Similarly, PV panel with 20 % panel efficiency, 5kW total power and 15 m 2 surface area, 4240 kWh electricity energy was generated. Annual energy consumption of the polyclinic was calculated 26107.52 kWh by using EnergyPlus software. To meet heating and cooling loads of the polyclinic, the air source heat pump was preferred. 8.51 % of the total demand can be supplied from wind turbine and 16.24 % by photovoltaic panels. The proposed wind-solar hybrid system for investigated region is not applicable due to low of the wind energy potential of the investigated region, the high price of the wind turbine and the proximity to the lifetime of the utilized components in the system to depreciation time. On the other hand, by using only photovoltaic panels system to generate electricity, it was determined that depreciation time will decrease from 17 to 11 years.

The most commonplace natural flow inside one-ended inclined pipes today is water heating systems. In this study, a model was created for the estimation of the pipe outlet temperature of the fluid with the energy balance for the inside of the tank, flow rate calculation of natural circulation, and other thermal calculations in a one-ended inclined pipe. In addition, this model has been compared with the Li model in the literature, and it is easier and more successful. 100, 200, 400, 600, and 800 W thermal power was applied to a one-ended inclined pipe, and the temperature values were recorded in 5-minute periods in the experiments that lasted a total of 6 hours. As the average of the experiments, the estimation results for the current model and the Li model are as follows: The average percent relative error rates are 6.02 and 15.1 and the coefficient of determination (R2) are 0.9865 and 0.9683, respectively.