Yazar "Celik, Erdal" seçeneğine göre listele
Listeleniyor 1 - 15 / 15
Sayfa Başına Sonuç
Sıralama seçenekleri
Öğe Comparison of Different Cooling Options for Photovoltaic Applications(Ieee, 2018) Ozkul, Feyzullah Behlul; Kayabasi, Erhan; Celik, Erdal; Kurt, Huseyin; Arcaklioglu, ErolA temperature increase plays a negative role on photovoltaic (PV) panel conversion efficiency by increasing recombination rates. In this study, air- and water-cooling options were simulated to investigate the efficiency behavior of a specific PV panel made of heterojunction Silicon (Si) whilst PV panel was cooling in operation by using ANSYS-FLUENT. For air cooling, two different options were suggested: air cooling with four different flow speeds and air cooling with a heat sink addition with three different flow speeds. As for water-cooling three flowrates were considered. Temperature distributions of PV panels for the all cooling options were demonstrated as a function of flow velocity of air and flowrate of water for different cooling conditions and compared with each other. The influence of temperature difference on panel conversion efficiency were also discussed. As a result, heat sink with a proper flow arrangement cooling option showed the best performance in terms of minimum material, minimum cost and minimum complexity with the 42 degrees C, 38.4 degrees C, 35.9 degrees C average surface temperatures and 20.9%, 21.3%, 21.5% panel efficiencies.Öğe Determination of cutting parameters for silicon wafer with a Diamond Wire Saw using an artificial neural network(Pergamon-Elsevier Science Ltd, 2017) Kayabasi, Erhan; Ozturk, Savas; Celik, Erdal; Kurt, HuseyinAn Artificial Neural Network (ANN) simulation was utilized to predict surface roughness values (R-a) for a Silicon (Si) ingot cutting operation with a Diamond Wire Saw (DWS) cutting machine. Experiments were done on a DWS cutting machine to obtain data for training, testing and validation of the ANN. The DWS cutting operation had three parameters affecting surface quality: spool speed, z axis speed and oil ratio in a coolant slurry. Other parameters such as wire tension, wire thickness, and work piece diameter were assumed as constant. The DWS cutting machine performed 28 cutting operations with different values of the selected three parameters and new cutting parameters were derived for different cutting conditions to achieve the best surface quality by using the ANN. Wafers 400 mu m thick were cut from a n-type single crystalline Si ingot in a STX 1202 DWS cutting machine. R-a values were measured three times from different regions of the wafers. In ANN simulation 70% of R-a values were used as training, 15% of R-a values were used as validation and 15% of R-a values were used to test data in ANN. The ANN simulation results validated training output data with success above 99%. Consequently, the R-a values corresponding to the cutting parameters, and also proper cutting parameters for specific R-a values were determined for DWS cutting using the ANN. (C) 2017 Elsevier Ltd. All rights reserved.Öğe Determination of lapping parameters for silicon wafer using an artificial neural network(Springer, 2018) Ozturk, Savas; Kayabasi, Erhan; Celik, Erdal; Kurt, HuseyinAn artificial neural network (ANN) simulation was utilized to determine the lapping parameters such as rotation speed, lapping duration and lapping pressure under a constant slurry supply for n-type crystalline Silicon (c-Si) wafers. Experiments were done with a Logitech PM5 lapping and polishing machine to obtain input data and target data for training, testing and validation of ANN. Lapping operation had five main parameters affecting surface quality: rotation speed, lapping duration, lapping pressure, flowrate of abrasive slurry and particle size in abrasive slurry. However, in this study slurry flowrate was assumed constant due the researches performed before. 218 lapping operations were performed with different values of the selected parameters and new lapping parameters were derived for different lapping conditions to achieve the best surface quality by using an ANN. In this study, wafers in 400 A mu m thickness cut under identical conditions from n-type single c-Si ingot in a STX 1202 DWS cutting machine were employed. Surface roughness (R (a) ) values were measured three times from different points of the wafers after lapping with a contact type surface roughness measurement tool using a microscopic scale stylus profiler (SP). In ANN simulation 70% of R (a) values were utilized for training, 15% of R (a) values were utilized for validation and 15% of R (a) values were utilized for test data. Results obtained from ANN simulation validated with a success above 99%.Öğe Determination of micro sized texturing and nano sized etching procedure to enhance optical properties of n-type single crystalline silicon wafer(Springer, 2017) Kayabasi, Erhan; Kurt, Huseyin; Celik, ErdalCrystalline silicon (c-Si) wafer was manufactured by applying micro texture and nano etching process without lapping and polishing for solar cell applications. Before micro texture and nano etching, wafers were exposed to chemical polishing process in high concentrated alkaline solution to remove saw damages and obtain a surface with low surface roughness (R-a). Uniform pyramidal structures were formed in alkaline solution. On pyramidal structures, nano sized porous shapes were formed by using Ag nano particles via wet chemical etching method. Micro textured and nano etched surface formed without any chemical mechanical (CM) lapping and polishing step, examined by Scanning Electron Microscope (SEM) for surface structure and UV-visible spectrometer for reflectance and absorbance measurements. Considerably good uniform porous surface with low reflectance was formed and compared with usual solar wafers produced with CM lapping and polishing. Furthermore, present process for preparing solar cell provides low cost, short time and less material consumption by removing lapping and polishing steps from overall process. Reflectance values were measured between 7 and 10% for best micro textured and nano etched c-Si wafers, respectively. Absorbance values were measured 0.4 and 1.2% for best micro textured and nano etched c-Si wafers, respectively. Curves of versus indicated the optical band gaps almost 1.12 e.V. for all wafers cut from same n-type single c-Si ingot.Öğe Effects of Electrical Properties on Determining Materials for Power Generation Enhancement in TEG Modules(Springer, 2019) Ozturk, Turgut; Kilinc, Enes; Uysal, Fatih; Celik, Erdal; Kurt, HuseyinThis study aimed to increase the energy efficiency of thermoelectric generators designed by considering the electrical properties of p- and n-type semiconductor materials for reducing the costs associated with the experiments, errors, and long production processes. Accordingly, the estimation of the energy amount to be produced by the thermoelectric materials was achieved by different doping elements using three different parameters such as skin-depth, electrical conductivity and dielectric constant. Additionally, the findings were supported by experimental results. In contrast to the conventionally used black-box type approach and estimation methods, an inference was obtained on the actual values of the materials.Öğe Estimating Seebeck Coefficient of a p-Type High Temperature Thermoelectric Material Using Bee Algorithm Multi-layer Perception(Springer, 2017) Uysal, Fatih; Kilinc, Enes; Kurt, Huseyin; Celik, Erdal; Dugenci, Muharrem; Sagiroglu, SelamiThermoelectric generators (TEGs) convert heat into electrical energy. These energy-conversion systems do not involve any moving parts and are made of thermoelectric (TE) elements connected electrically in a series and thermally in parallel; however, they are currently not suitable for use in regular operations due to their low efficiency levels. In order to produce high-efficiency TEGs, there is a need for highly heat-resistant thermoelectric materials (TEMs) with an improved figure of merit (ZT). Production and test methods used for TEMs today are highly expensive. This study attempts to estimate the Seebeck coefficient of TEMs by using the values of existing materials in the literature. The estimation is made within an artificial neural network (ANN) based on the amount of doping and production methods. Results of the estimations show that the Seebeck coefficient can approximate the real values with an average accuracy of 94.4%. In addition, ANN has detected that any change in production methods is followed by a change in the Seebeck coefficient.Öğe High performance Ca3-xAg0.3LaxCo4O9 materials for aerospace applications of thermoelectric devices(Springer, 2024) Sari, Mucahit Abdullah; Kilinc, Enes; Uysal, Fatih; Kurt, Huseyin; Celik, ErdalIn the domain of aviation applications, the utilization of thermoelectric materials holds significant importance, particularly in regions characterized by notable thermal gradients, aimed at harnessing these gradients for electricity generation. This study advocates for the adoption of thermoelectric modules, specifically within the operational contexts of fixed-wing aircraft and satellites. These settings require resilient thermoelectric systems capable of effectively exploiting temperature differentials to enable electrical power generation, thus emphasizing the necessity of integrating such modules into their operational frameworks. Accordingly, this paper systematically elucidates the production and characterization of Ca3-xAg0.3LaxCo4O9 for thermoelectric applications in the aerospace sector. Ca3-xAg0.3LaxCo4O9 ceramics are synthesized via the sol-gel method employing Ca, Ag, La, and Co precursor materials. Distilled water serves as the solvent to dissolve the precursors, yielding homogeneous solutions. These solutions undergo magnetic stirring at 100 degrees C to achieve final homogeneity, with citric acid monohydrate introduced as a chelating agent to expedite xerogel formation. pH and turbidity measurements are conducted on the prepared solutions using a pH meter and turbidimeter, respectively. Following the gelation process, the resulting xerogel is dried at 200 degrees C for 2 h to eliminate moisture and undesirable gases. Subsequently, the dried powders are calcined at 800 degrees C for 2 h, yielding the final Ca3-xAg0.3LaxCo4O9 materials. The thermal, structural, microstructural, and thermoelectric properties of the materials are comprehensively characterized utilizing DTA-TG, FTIR, XRD, XPS, SEM, and thermoelectric measurement machines. It is ascertained that the produced semiconducting ceramic materials exhibit efficient suitability for thermoelectric generator production.Öğe High temperature thermopower of sol-gel processed Zn1-x-y Al x Me y O (Me: Ga, In)(Springer, 2017) Kilinc, Enes; Demirci, Selim; Uysal, Fatih; Celik, Erdal; Kurt, HuseyinIn this study, dually doped samples of Zn1-x-y Al (x) Me (y) O (Me: Ga, In) were prepared by sol-gel process followed by hot isostatic pressing for high temperature thermoelectric applications. Material characterizations were performed with differential thermal analysis-thermogravimetry, Fourier transform infrared spectroscopy and X-ray diffraction on the target phases. Successful doping of the samples was confirmed by X-ray photoelectron spectroscopy and energy dispersive X-ray analysis. Thermopower values of the samples are found to be relatively high in analogy to semiconducting behavior in which negative values indicate electrons are the dominant charge carriers (n-type). Substitution of Zn2+ by Ga3+ and In3+ for Zn1-x-y Al (x) Me (y) O (Me: Ga, In) increases electron concentration in the samples and thereby decreases the thermopower values compared to Zn0.98Al0.02O. Considering the absolute values, In doped samples have higher thermopower (alpha (max) = -162 A mu V/K at 585 A degrees C for Zn0.96Al0.02In0.02O) compared to the Ga doped sample. Al and In dually doped Zn0.96Al0.02In0.02O could be considered as a promising n-type thermoelectric material for high temperature applications.Öğe High-Temperature Thermoelectric Properties of Sol-Gel Processed Ca2.5Ag0.3RE0.2Co4O9 (RE: Y and Rare-Earths) Materials(Wiley-V C H Verlag Gmbh, 2020) Kilinc, Enes; Uysal, Fatih; Celik, Erdal; Kurt, HuseyinHerein, dually doped Ca2.5Ag0.3RE0.2Co4O9 (RE: La, Pr, Nd, Sm, Gd, Dy, Er, Yb, Eu, Tb, Ho, Lu, Ce, and Y) samples are synthesized by sol-gel technique and consolidated by cold pressing under high pressure to systematically scrutinize the influences of Y and rare-earth dually doping with Ag on transport properties of Ca3Co4O9 for high-temperature thermoelectric (TE) applications. Characterization results reveal that targeted phase is successfully produced, and doping of the compositions is provided. Doping of Y and rare-earth elements together with Ag into the Ca2+ site is effective in increasing the Seebeck coefficient and decreasing the electrical resistivity of the samples, thanks to the reduction in carrier concentration. Thermal conductivity of the samples is reduced related to the lower relative densities and alloy scattering originated from dually doping. Among the samples, Ca2.5Ag0.3Ho0.2Co4O9 and Ca2.5Ag0.3Eu0.2Co4O9 exhibit the highest power factor (PF) values of 0.65 and 0.62 mW m(-1) K-2 at 800 degrees C, respectively. These results are quite high for bulk oxide TE materials which can be assessed as potential oxide TE materials for high-temperature TE power generation.Öğe Investigating the Effects of Cooling Options on Photovoltaic Panel Efficiency: State of the Art and Future Plan(Ieee, 2018) Ozkul, Feyzullah Behlul; Kayabasi, Erhan; Celik, Erdal; Kurt, Huseyin; Arcaklioglu, ErolCurrently, cooling of photovoltaic (PV) panels, a significant issue due the negative effect on panel efficiency, is subjected to intensive researches. For this purpose, numerous researches on cooling methods are performed to keep the panel efficiencies around the design values. In this study, a comprehensive literature review was presented to give the status of the technological improvement in cooling options. In addition, strong and weak aspects of the studies were discussed, and advantageous methods were emphasized for the further application of PV panels. Finally, future perspective of PV panel cooling studies was explored with proper cooling options in lower operating temperatures for higher operation efficiencies.Öğe A prediction model of artificial neural networks in development of thermoelectric materials with innovative approaches(Elsevier - Division Reed Elsevier India Pvt Ltd, 2020) Kokyay, Seyma; Kilinc, Enes; Uysal, Fatih; Kurt, Huseyin; Celik, Erdal; Dugenci, MuharremThe fact that the properties of thermoelectric materials are to be estimated with Artificial Neural Networks without production and measurement will help researchers in terms of time and cost. For this purpose, figure of merit, which is the performance value of thermoelectric materials, is estimated by Artificial Neural Networks without an experimental study. P-and n-type thermoelectric bulk samples were obtained in 19 different compositions by doping different elements into Ca2.7Ag0.3Co4O9- and Zn0.98Al0.02O-based oxide thermoelectric materials. The Seebeck coefficient, electrical resistivity and thermal diffusivity values of the bulk samples were measured from 200 degrees C to 800 degrees C with an increase rate of 100 degrees C, and figure of merit values were calculated. 7 different Artificial Neural Network models were created using 123 measured results of experimental data and the molar masses of the doping elements. In this system aiming to predict the electrical resistivity, thermal diffusivity and figure of merit values of thermoelectric materials, the average R value and accuracy rate of these values were estimated to be 94% and 80%, respectively. (c) 2020 Karabuk University. Publishing services by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Öğe Prediction of nano etching parameters of silicon wafer for a better energy absorption with the aid of an artificial neural network(Elsevier Science Bv, 2018) Kayabasi, Han; Ozturk, Savas; Celik, Erdal; Kurt, Huseyin; Arcaldioglu, ErolTo enhance energy absorption of photovoltaics, several etching experiments with various parameters were performed. In addition, an Artificial Neural Network (ANN) simulation was utilized to predict chemical nano etching parameters such as masking and etching durations for Silicon (Si) solar cell applications to reach minimum surface reflectance in an optimum etching duration. Experiments were performed with different masking and etching durations to determine the characteristics of surface reflectance of micro textured n-type single crystalline Si wafers in 25mmx25mm width and 300 gm thickness to provide training data for ANN. For this purpose, solutions with identic properties including Ag nanoparticles were applied with different application durations on the surfaces of n-type single crystalline Si wafers to cover partially the Si surfaces with Ag nano-particles at masking step. After, partially masked Si surfaces were exposed to chemical nano etching to develop nano-sized porous structures under different etching durations in an identic acidic etching solution. For the etching of Si wafers, 32 masking and etching processes were performed. Reflectance measurements and SEM images were evaluated to determine the optimum etching duration resulting the best surface quality with minimum reflectance. In addition, reflectance values were utilized as input data for training, testing and validation steps of developed ANN. In the ANN simulation, 70% of reflectance values were used as training, 15% of reflectance values were used as validation and 15% of reflectance values were used to test data in the ANN. Consequently, surface reflectance values under different masking and etching durations were predicted with the new parameter set by using the trained ANN with a success level above 99%.Öğe Production and development of ZnAlGeO semiconducting materials for thermoelectric generators in potential aerospace applications(Springer, 2024) Sari, Mucahit Abdullah; Kilinc, Enes; Uysal, Fatih; Kurt, Huseyin; Celik, ErdalThis research aims to produce and develop semiconducting thermoelectric materials for thermoelectric generators in aerospace applications. In this context, ZnAlGeO powders were synthesized via the sol-gel method using precursor materials and a 20% toluene solution in ethanol as the solvent. Glacial acetic acid was added to accelerate gel formation. The pH and turbidity values of prepared solutions were measured using a pH meter and turbidimeter. After gelation, the obtained xerogel was dried at 200 degrees C for 9 h to remove moisture and undesired gases. Dried powders were calcined at 600 degrees C for 4 h in air, resulting in final ZnAlGeO materials. The pellets underwent thermal processing for 36 h at a temperature of 1350 degrees C, targeting the production of bulk samples within the n-type semiconductor category. Extensive characterization, including thermal, structural, microstructural, and thermoelectric properties, was conducted using various techniques such as DTA-TG, FTIR, XRD, XPS, SEM, and thermoelectric measurement devices. The study concludes that the produced semiconducting ceramic materials exhibit efficiency for thermoelectric generator production. Zn1-x-yAlxGeyO (x = 0.02, 0.04, and y = 0.02, 0.04) powders were synthesized by sol-gel method and densified under high-pressure cold pressing.Effects of dual doping on thermoelectric properties of Zn1-x-yAlxGeyO (x = 0.02, 0.04, and y = 0.02, 0.04) were investigated.Thermoelectric performances of Zn1-x-yAlxGeyO (x = 0.02, 0.04, and y = 0.02, 0.04) are enhanced by dual doping.Promising Zn1-x-yAlxGeyO (x = 0.02, 0.04, and y = 0.02, 0.04) oxide materials for energy harvesting and conversion technologies, particularly in aerospace applications.Öğe Steady-state thermal-electric analysis of a ?-shaped 8-pair thermoelectric generator(Elsevier Science Bv, 2019) Kilinc, Enes; Uysal, Fatih; Celik, Erdal; Kurt, HuseyinIn this study, steady-state thermal-electric analysis of a pi-shaped 8-pair TEG was performed by finite element method using thermal-electric module in Ansys Workbench for high temperature applications. TE powders of Ca2.7Ag0.3Co4O9 and Zn0.94Al0.04In0.02O were synthesized by sol-gel method followed by cold pressing (CP) to obtain bulk samples. High temperature thermoelectric properties of the bulk samples were used for p- and n-type legs, respectively. In the model, a Delta T temperature difference of 400 degrees C was applied to obtain a high temperature power output. As a result of the thermal-electric analysis, temperature distribution and total current density along the TEG were evaluated. (C) 2019 Elsevier Ltd. All rights reserved.Öğe A sustainable cooling/lubrication method focusing on energy consumption and other machining characteristics in high-speed turning of aluminum alloy(Elsevier, 2024) Korkmaz, Mehmet Erdi; Gupta, Munish Kumar; Celik, Erdal; Ross, Nimel Sworna; Gunay, MustafaUnderstanding energy implications and machining performance standards is vital as industries move toward sustainability. Modern machining techniques including high-speed turning are used in the study on aluminum alloy materials. Therefore, this study focuses on the energy consumption and in-depth analysis of machinability criteria in the context of eco-friendly high-speed turning of aluminum alloy. The experiments were performed under ecofriendly cutting conditions dry and minimum quantity lubrication (MQL) conditions and the intricate relationship between machining parameters and cooling conditions was investigated in terms of energy consumption, tool wear, surface roughness and chips morphology. The result reveal that the Ra values exhibited 2.4 times increase in dry machining and an average increase of 2.3 times in MQL machining when the feed rate was increased from 0.2 to 0.4 mm/rev. Moreover, the MQL cooling is helpful in lowering the energy consumption as well as tool wear and surface roughness during the machining operations. MQL machining resulted in a 35% reduction in flank wear and 20% reduction in energy consumption compared to dry machining.
