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Öğe Optimum insulation thickness assessment of different insulation materials for mid-latitude steppe and desert climate (BSH) region of India(Journals & Books, 2021-01) Kallioğlu, Mehmet Ali; Sharma, Ashutosh; Chinnasamy, Veerakumar; Chauhan, Ranchan; Singh, TejOne of the most effective techniques that is used for energy wastage in buildings is heat insulation. It is possible due to this application to minimize the fuel quantity and accordingly tolerate toxic emissions by finding the optimum point that gives the maximum efficiency. This study was conducted for Jaipur province in Indian climate geography. Climatic characteristics of the region are Mid-Latitude Steppe and Desert Climate (Bsh). Energy need and heat losses in exterior wall were determined by accepting cooling degree day value as T > 24 °C. Optimum insulation thickness, payback period, annual return and annual return rate for XPS and EPS of two different insulating materials respectively are 0.0383–0.0731, 2.35–1.79, 10.95–12.92, 46.84–37.25.Öğe A review of phase change materials (PCMs) for thermal storage in solar air heating systems(Journals & Books, 2021-01) Kallioğlu, Mehmet Ali; Sharma, Ashutosh; Chauhan, Ranchan; Chinnasamy, Veerakumar; Singh, TejThe surging energy requirements and greenhouse gas (GHG) emission have directed the research towards the utilization of renewable energy sources especially solar energy. Most of the energy part in domestic and commercial consumption is utilized for air heating and drying which can be improved significantly by utilizing solar air heating applications. The main drawback associated with the solar air heating system (SAHS) is the fluctuation in the availability of solar radiations which can be mitigated by a greater extent with the help of thermal storage. Phase change materials (PCMs) are generally utilized for latent heat storage. The present study reviews the various PCMs utilized in thermal storage with SAHS. Numerous types of PCM materials, their properties and applications in solar air heating system have been reviewed. Heat transfer characteristics enhancement techniques like encapsulation, extended surfaces and conductive particle dispersion have also been studied. The air conditioning demands in the future could be significantly mitigated by utilizing these materials.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.
