3 sonuçlar
Arama Sonuçları
Listeleniyor 1 - 3 / 3
Öğe Effects of ethanol addition to biodiesel fuels derived from cottonseed oil and its cooking waste as fuel in a generator diesel engine(Taylor & Francis, 2020-03) Karakaya, HakanExploration of energy sources such as renewable and non-edible vegetable oils has been continued during the recent two decades of 2000s. Cottonseed oil is a non-edible, abundant oil and is generally used as cooking oil. In the present study, the usability of biodiesel derived from both cottonseed oil and its cooking wastes was investigated by blending them with ULSD or ethanol in 50 percentages. B50, WB50, B50E50 and WB50E50, biodiesel and ethanol-contained fuels and ULSD were prepared for experiments. Combustion, performance, and emissions tests were conducted on a diesel engine used for power-producing electrical generator. In the combustion tests, cylinder pressure, HRR, CHR, MGT, and MFB were analyzed while MFC, BSFC, exhaust manifold temperature, and thermal efficiency were obtained in the performance tests. In the emissions tests, CO, HC, and NOx emissions were measured and compared with the results of ULSD. Combustion and performance findings of ULSD contained biodiesel blends were found more similar to those of ULSD. The duration of combustion stage can clearly be seen to be narrowed for ethanol-contained blend because of the rabid combustion characteristics of ethanol. Besides, the peak of HRR was found 10% higher for B50E50 while it was found averagely 8% for WB50E50 blends. NOx emissions were found 48% lower averagely for ethanol contained biodiesel blends that it is the most important finding of ethanol using with biodiesel. Besides, HC emissions were also found about 75% for biodiesel contained diesel fuel blends.Öğe Empirical calculation of the optimal tilt angle for solar collectors in northern hemisphere(Taylor & Francis, 2020-03) Karakaya, Hakan; Kallioğlu, Mehmet Ali; Durmuş, Aydın; Yılmaz, AdemPanel tilt angles (0°–90°) need to be in a proper position and location to get maximum productivity from solar energy. Values used in solar energy applications are generally computed by (global, diffuse, and direct) variation on horizontal surfaces calculated using isotropic sky and a mean albedo method. Being parallel to the available literature concerning such applications, this study focuses on the optimum solar panel angle. In this study, optimum solar panel angle value by months was determined for three sample provinces (Antalya, Kayseri, and Trabzon) first and North Hemisphere then. Capacity calculation of sample provinces was performed based on monthly, seasonal, and annual angle values and horizontal situation. Monthly and annual optimum angle values for Northern Hemisphere by 1° increase for between the latitudes of 1° N and 65° N. While the panel angle is at the highest level in autumn and winter (November-December-January and February) in annual process, the lowest angle is observed in spring and summer (May-June-July-August). Several different mathematical models have been developed for the sample provinces and Northern Hemisphere. While the variable of 12 different models that were developed for provinces is the Declination (δ) coefficient, the variable of 7 different models that were developed Northern Hemisphere is the latitude (Ø). Regional values in literature with estimation results of models were analyzed based on NASA and PVGIS data color scale. There was created a possibility of comparison by aligning all the optimum solar panel angle values of related location via a scale whose values vary by 1 and 10. Moreover, all the models were verified by statistical analysis methods. R2 (determination coefficient) in 19 different estimation equations is pretty close or equal to 1. However, the best among them is Eq. 32 (0.9979) for sample provinces and Eq. (33) (1) for the Northern Hemisphere; developed models are less-than-stellar. Other statistical data of these equations are MBE (−0.0616), RMSE (1.1176), t-sat (0.1830), Bias (1). For Eq. (32); MBE (1.96), RMSE (2.75), t-sat (8.13), MPE % (3.98), MAPE (5.87), SSRE (0.27), and RSE (0.06) for Eq. (33). The statistical analyzes indicate that all regression models are applicable in Turkey and Northern Hemisphere. Developed all correlations are recommended for academic and industrial users.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.
