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Öğe Energy, economic and environmental analysis and comparison of the novel Oxy- combustion power systems(Yildiz Technical Univ, 2022) Ozsari, Ibrahim; Ust, YasinOxy-combustion technologies are clean energy systems with zero emission; they have great potential when considering global warming and climate change. This study presents a detailed thermodynamic analysis in terms of energy, environment, and economy. Consequently, the results obtained for an oxy-combustion power system are presented in comparison with a conventional gas turbine power system. The results are presented as a function of the pressure ratio with regard to net power, input heat, system efficiency, specific fuel consumption, equivalence ratio, fuel-air ratio, capital investment cost, fuel cost, oxygen cost, total cost, electricity revenue, and net profit. In addition, the study calculates the pollutant emissions from non-oxy-combustion systems and investigates the environmental costs. The pressure ratio for maximum net power has been obtained as 20.8 in the conventional gas turbine power system. Similarly, the pressure ratios for maximum net power in oxy-combustion power cycles with 26%, 28%, and 30% oxygen ratios are 23.3, 27.4 and 29.7, respectively. Results from 24% to 30% have been displayed to observe the effect of reactant oxygen in the oxy-combustion power cycles. The optimum cycle conditions have been determined by calculating the costs of system components, total revenues, and net profits at pressure ratios of 10, 20, 30 and 40. Finally, the results reveal the pressure ratio should be reduced to minimize the total costs per cycle. For maximum net profit, the pressure ratio in a conventional gas turbine power cycle has been calculated as 15.9; similarly, the pressure ratios in oxy-combustion power cycles with 26%, 28%, and 30% oxygen ratios have been respectively calculated as 12.8, 15.2 and 16.4.Öğe Exergetic performance analysis and comparison of oxy-combustion and conventional gas turbine power cycles(Yildiz Technical Univ, 2023) Ozsari, Ibrahim; Ust, Yasin; Karakurt, Asim SinanOxy-combustion technologies are green energy systems and an impressive solution to climate change and global warming. This study presents a detailed exergy analysis obtained for oxy-combustion power systems in comparison with a conventional gas turbine power system. The results include net power, overal thermal efficiency, exergy destruction, exergy efficiency, power density, exergetic performance coefficient (EPC), ecological performance coefficient (ECOP), effective ecological power density (EFECPOD), and mean exergy density (MED), and cost of power density (COPD), which are calculated as functions of pressure and oxygen ratios. The conventional gas turbine power system obtained a pressure ratio for maximum net power of 20.8. Similarly, oxy-combustion power cycles at 26%, 28%, and 30% oxygen ratios have respective pressure ratios for maximum net power of 23.3, 27.4, and 29.7. Results from 24%-30% oxygen ratios are displayed to show the reactant oxygen's effect on the oxy-combustion power cycles. Increases in the pressure ratio show decreases in the total exergy destruction in both the conventional gas turbine power system and the oxy-combustion power systems. Meanwhile, increases in the pressure ratio show increases in the total efficiency, power density, exergy efficiency, EPC, EFFECPOD, and MED in both the conventional gas turbine and the oxy-combustion power systems. In addition, increases in the oxygen ratio in the oxy-combustion power systems show different characteristics for these parameters based on the pressure ratio of the cycle. In terms of COPD, conventional gas turbine power systems are more advantageous than oxy-combustion power systems. Optimum COPD is obtained at a pressure ratio of 25.6.Öğe Historical research trends and overview about exergy: a comprehensive analysis(Inderscience Enterprises Ltd, 2023) Ozsari, IbrahimThis study examines the contributions of researchers from around the world in the field of exergy over the past 30 years (1/1/1992-1/1/2022). Various aspects of the studies have been analysed such as publication type, research areas, and keywords. In addition, countries, authors, journals, and institutions that have worked in the field of exergy were examined. Thus, the detailed results of the five most influential authors, seven journals, and 15 institutions in the field of exergy in terms of publication, citation, PIP, and h-indexes are presented over the years. The effects of all countries broadcasting from the field of exergy in terms of publication and citation are shown. As a result of the analysis of all parameters, it has been shown that the most effective countries are China, Iran, and Turkey. Besides, it has been determined that Dr. Ibrahim Dincer is the most influential author in the terms of contributing authors.Öğe Predicting main engine power and emissions for container, cargo, and tanker ships with artificial neural network analysis(Univ Zagreb Fac Mechanical Engineering & Naval Architecture, 2023) Ozsari, IbrahimThe most significant aspect of international shipping is sea transportation, and the developments to be made in maritime transport will inspire and predict all other fields. Therefore, determining a ship's main engine power has great importance in terms of both energy efficiency and environmental factors. The maritime transport and shipping industry has currently begun to understand the importance of artificial intelligence technology. This study uses an artificial neural network (ANN) model to predict the main engine power and pollutant emissions of container, cargo, and tanker ships over 14 parameters: maximum speed, average speed, breadth, year built, ship type, status, length overall (LOA), light displacement, summer displacement, fuel type, deadweight tonnage (DWT), gross tonnage, engine cylinder size, and engine stroke length. In order to provide accurate results, the ANN analysis was trained with data from 3,020 ships, which is quite high compared to the studies in the literature. Many ANN models have been developed and compared to achieve minimal errors and highest accuracy in the results. The regression values, which involve the training, validation, and test values for the different ship types, were obtained as 0.99773 for container ships, 0.98964 for cargo ships, and 0.97755 for tanker ships, with a value of 0.97189 for all ships. The ANN structure was tested using many variations for hidden neuron counts, with the ANN analysis made with 30 neurons obtaining the best results. The ANN analysis results were compared with real values, which showed that very accurate results had been obtained according to the mean squared error (MSE), regression, and mean absolute percentage error (MAPE) results. The MSE value had exceeded 20,000 in the two-input ANN model, but decreased to 0.03, 0.081, and 0.13 with the 14-input model for container, cargo, and tanker ships, respectively. In order to make accurate predictions with maximum precision in the ANN analyses, the study attempted to use different values for the numbers of hidden neurons and inputs and then presented the performance results. The developed model can be used in future studies to be done on fuel consumption and energy efficiency for ships in maritime transport.Öğe Predicting tanker main engine power using regression analysis and artificial neural networks(Yildiz Technical Univ, 2023) Gunes, Umit; Bashan, Veysi; Ozsari, Ibrahim; Karakurt, Asim SinanThe purpose-oriented design and planning of ships is maintained throughout production. Outer form of ship equipment starts with the steel construction process. The outer body production process moves ahead with painting, quality control tests, and bureaucratic procedures. In accordance with all these form and block operations, choosing a main engine suitable for all other technical parameters is vital, especially regarding ship speed and the amount of cargo it will carry. As a result, estimating main engine power is attempted with the help of artificial neural network (ANN) and regression analyses by considering a ship's technical parameters (e.g., draught, depth, deadweight tonnage [DWT], gross tonnage [GT], and engine power). This study conducts regression and ANN analyses over 836 tanker ships from the Marine Traffic database to predict main engine power using input parameters (deadweight (DWT), Length (L), Breadth (B), and gross ton (GT) values). The regression analyses show Model7 to perform the best approximation with a determination value = 0.827 usable for estimating main engine power. After all the examinations, a very accomplished result of 0.98047 was additionally obtained from the ANN analysis. The study makes beneficial and innovative contributions to predicting tankers' required main engine power.Öğe The effects of different working fluids on the performance characteristics of the Rankine and Brayton cycles(Elsevier Ltd, 2024) Kanberoğlu, Berna; Ozsari, Ibrahim; Dobrucali, E.; Gonca, GuvenIn this study, 143 different working fluids have been analyzed for Rankine and Brayton cycles in terms of performance characteristics such as power, thermal and exergy efficiency, and EFECWOD. The selection of working fluid is a significant consideration in the design of both these cycles, as it can importantly affect the performance and efficiency of the system. As of late, there has been growing interest in investigating the effects of various working fluids on the performance characteristics of these cycles. This article aims to determine the ten best among different working fluids according to the determined criteria using the Technique for Order of Preference by Similarity to Ideal Solution, which is a multi-criteria decision method. In the decision-making process, the importance scale of the analytical hierarchy process was used to determine the weight values of the criteria to be used in the TOPSIS analysis to obtain more accurate results. Artificial Neural Network method is employed to identify the optimal working fluid as well. As a conclusion of this thermodynamic analysis of the performance characteristics for Rankine and Brayton cycles using various working fluids, the Rankine cycle achieved the maximum power of 12,277 kW, the maximum efficiency of 93 %, and the maximum EFECWOD value of 9962 kJ/m3 with hydrogen, helium, and dimethylcarbonate as the respective working fluids. Furthermore, hydrogen exhibits the highest power output of 2493 kW in the Brayton cycle. Nitrogen demonstrates the highest efficiency at 44 %, while R141b achieves the highest exergy efficiency at 98 %. Lastly, the fluid with the highest EFECWOD value is R13, with a measurement of 4932 kJ/m3. © 2023 Hydrogen Energy Publications LLCÖğe Trend analysis and evaluation of hydrogen energy and hydrogen storage research(Wiley, 2023) Ozsari, IbrahimHydrogen energy is a type of energy contained in hydrogen, the most common element in the universe. Hydrogen energy is a clean form of energy used in many other fields apart from powering spacecraft and cars. This study examines the contributions researchers from around the world have made in the field of hydrogen energy and storage over the past 30 years (January 1, 1992-January 1, 2022). A comprehensive bibliometric approach has been applied to illustrate the scientific publications on hydrogen energy and related topics using the Scopus database, which revealed 15 792 publications published by more than 500 authors and organizations scattered over 120 countries. Various aspects of these studies have been analyzed, such as publication type, number of citations, fundamental research areas, and keywords. The article additionally examines the countries, authors, journals, and institutions that have worked in the field of hydrogen energy and storage. Thus, this article presents detailed results from the 18 most influential authors, 20 most influential journals, and 15 most influential institutions in the field of hydrogen energy and storage in terms of publication, citation, publication impact parameters, and h-indexes over the past 30 years and shows the effects of all countries that have published in the field of hydrogen energy and storage in terms of number of publications and citations. As a result of the analysis of all parameters, the most effective journals are shown to be the International Journal of Hydrogen Energy, Fuel Cells Bulletin, and the Journal of Materials Chemistry A, and the most effective countries are seen to be China, USA, and South Korea. However, Ibrahim Dincer has been identified as the most influential author and to differ in several ways in terms of contributing authors. The results also indicate how important the subject of hydrogen energy is in the field of energy, physics and astronomy, and engineering. As a result, this article presents the trends over the last 30 years and details on future directions.
