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Öğe Şanlıurfa ilinde yatay yüzeye gelen anlık global güneş ışınımının modellenmesi(Dicle Üniversitesi, 2019-03-15) Karakaya, Hakan; Kallioğlu, Mehmet Ali; Avcı, Ali Serkan; Ercan, UmutBu çalışma ile Şanlıurfa ilinin iklim özellikleri ve topografik yapısı göz önüne alınarak yatay düzleme gelen aylık ortalama günlük global güneş radyasyonunun tespit edilebilmesi için literatürde yer alan 5 farklı model incelenmiştir. Sonuçlar istatistiksel karşılaştırma metotları, belirlilik katsayısı (R²), ortalama yüzde hata (MPE), sapma hatası (MBE), ortalama mutlak hata yüzdesi (MAPE), bağıl hata karesi (SSRE), bağıl standart hata (RSE), ortalama karekök hatası (RMSE), bağıl hata yüzdesi (e) ve t-istatistik (t-sat) ile olmak üzere dokuz farklı istatistik yöntemi ile karşılaştırılmıştır. Şanlıurfa ili için en uygun yaklaşım için bir sonuç verilmiştir. İstatistiksel hata sonuçlarına göre Cheegar ve Chibani Modeli yatay düzleme gelen global güneş ışınımı için Şanlıurfa ilinde kullanılacak en uygun model olarak belirlenmiştir. Sonuç olarak Şanlıurfa ili toplam güneş radyasyonu tahmini için polinom modelin tercih edilmesi önerilmiştir. Bu model verilerine göre Şanlıurfa ili için yıllık güneş enerjisi potansiyeli 4332,020 W/m2 /ay olarak belirlenmiştirÖğe Creating the optimum panel inclination angles of the southern aegean region(International Journal of Advances in Science Engineering and Technology, 2018-01) Karakaya, Hakan; Ercan, Umut; Kallioğlu, Mehmet Ali; Avcı, Ali Serkan; Genç, ÖmerValues that are used in solar energy applications are usually calculated by data for radiation reaching a horizontal plane. In order to achieve maximum efficiency in solar energy, panels must be at a suitable angle and position. This study determined monthly optimum panel angles for the Southern Aegean Region (Muğla) in Turkey and created three different correlations. In an annual course (January-December), panel angles varied in the order of 590 , 490 , 380 , 200 , 50 , 00 , 00 , 150 , 320 , 490 , 590 and 610 . The average annual panel inclination angle was 32.250 , and in the case of changing the angles monthly, the annual efficiency increased by 17.03% in comparison to horizontal position and reached the average annual radiation value of 5949 W/m2 -year. The best estimation model developed for the region was in the form of β . = 0,0002(δ) ଷ − 0,0092(δ) ଶ − 1,4379(δ) + 34,72. The statistical analysis values were R2 (0.9973), MBE (0.0031), RMSE (1.22) and t-sat (0.0085), while they successfully corresponded to the panel inclination values.Öğe Empirical modeling between degree days and optimum insulation thickness for external wall(Taylor & Francis, 2020-03) Karakaya, Hakan; Kallioğlu, Mehmet Ali; Ercan, Umut; Avcı, Ali Serkan; Fidan, CihatInsulating is the most effective method that is used to save energy in buildings. Samples from cities from different climatic zones from TS 825 (Turkey) first. Optimum insulation thickness () analysis is based on two types of insulating and four different fuels (natural gas, coal, fuel oil and electric) of related cities. Cost accounts, payback period and CO2-SO2 emission calculations were performed based on these analyses. Second of all, the relationship between a number of degree day (NDD) and optimum insulation thickness () was developed by linear, quadratic and cubic correlations. Thirty different mathematical correlations based on different fuel types by using XPS and EPS insulating materials. Twenty-four of these models that were developed were generated peculiar to the fuel type; six of them were generated based on average insulation thickness. R2 values of related correlations are between 0.9989 most and 0.9952 at least as well as it is pretty close to (R ≤ 1) one value. The model among these models is the cubic mathematical model that gives the best average value. a = 0.0036, b = 5E-05, c = – 7E-09 and d = 6E-13 are the values for XPS material. Following values are for EPS material; a = 0.0028, b = 5E-13, c = – 7E-09 and d = 4E-05. R2 determination coefficient of both two equations is pretty close to 0.9989 and 1; the models obtained are less-than-stellar. Optimum insulation thickness of the area can be known based on the type of material via the number of degree day without the need for long analyses. According to the R2 values, the use of all models is recommended for academic and industrial users.
