Yazar "Celebi, Kerimcan" seçeneğine göre listele

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    A NOVEL APPROACH TO THERMAL AND MECHANICAL STRESSES IN A FGM CYLINDER WITH EXPONENTIALLY-VARYING PROPERTIES
    (Polish Soc Theoretical & Applied Mechanics, 2017) Celebi, Kerimcan; Yarimpabuc, Durmus; Keles, Ibrahim
    A novel approach is employed to a general solution for one-dimensional steady-state thermal and mechanical stresses in a hollow thick cylinder made of a functionally graded material (FGM). The temperature distribution is assumed to be a function of radius, with general thermal and mechanical boundary conditions on the inside and outside surfaces of the cylinder. The material properties, except Poisson's ratio, are assumed to be exponentially-varying through the thickness. Forcing functions applied to the inner boundary are internal pressures which may be in form of steps. These conditions result in governing differential equations with variable coefficients. Analytical solutions to such equations cannot be obtained except for certain simple grading functions and pressures. Numerical approaches must be adopted to solve the problem in hand. The novelty of the present study lies in the fact that the Complementary Functions Method (CFM) is employed in the analysis. The Complementary Functions method (CFM) will be infused into the analysis to convert the problem into an initial-value problem which can be solved accurately. Benchmark solutions available in the literature are used to validate the results and to observe the convergence of the numerical solutions. The solution procedure is well-structured, simple and efficient and it can be readily applied to cylinders. It is also well suited for problems in which mechanical properties are graded.
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    A unified method for stresses in FGM sphere with exponentially-varying properties
    (Techno-Press, 2016) Celebi, Kerimcan; Yarimpabuc, Durmus; Keles, Ibrahim
    Using the Complementary Functions Method (CFM), a general solution for the one-dimensional steady-state thermal and mechanical stresses in a hollow thick sphere made of functionally graded material (FGM) is presented. The mechanical properties are assumed to obey the exponential variations in the radial direction, and the Poisson's ratio is assumed to be constant, with general thermal and mechanical boundary conditions on the inside and outside surfaces of the sphere. In the present paper, a semi-analytical iterative technique, one of the most efficient unified method, is employed to solve the heat conduction equation and the Navier equation. For different values of inhomogeneity constant, distributions of radial displacement, radial stress, circumferential stress, and effective stress, as a function of radial direction, are obtained. Various material models from the literature are used and corresponding temperature distributions and stress distributions are computed. Verification of the proposed method is done using benchmark solutions available in the literature for some special cases and virtually exact results are obtained.
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    Energy and exergy analysis of biodiesel
    (Elsevier Science Bv, 2017) Ozcanli, Mustafa; Serin, Hasan; Calik, Ahmet; Celebi, Kerimcan; Akar, M. Atakan
    [Abstract Not Available]
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    Evaluation of fuel consumption and vibration characteristic of a compression ignition engine fuelled with high viscosity biodiesel and hydrogen addition
    (Pergamon-Elsevier Science Ltd, 2017) Celebi, Kerimcan; Uludamar, Erinc; Ozcanli, Mustafa
    Viscosity property of a fuel is a crucial point for internal combustion engine characteristics. Performance and emission parameters as well as injector's life of an engine is primarily effected by viscosity of the fuels. In present study, effect of high viscosity biodiesel fuels with hydrogen addition was investigated in a compression ignition engine. Biodiesels that are produced from Pongamia Pinnata and Tung oils were used as pure biodiesels as well as blended with low sulphur diesel fuel at the volume ratios of 50% and 75%. Furthermore, hydrogen gas was injected into intake manifold in order to evaluate its effect with the usage of high viscous liquid fuels. The results revealed that brake specific fuel consumption was increased with biodiesel fuels, whereas hydrogen addition into intake manifold improved the consumption. Total vibration acceleration of the engine reduced with biodiesel and hydrogen additions. Frequency spectrum indicated that this decrement was primarily lowered due to less energy transmitted through engine pistons that converted from chemical energy of fuels. (C) 2017 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
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    Experimental and artificial neural network approach of noise and vibration characteristic of an unmodified diesel engine fuelled with conventional diesel, and biodiesel blends with natural gas addition
    (Elsevier Sci Ltd, 2017) Celebi, Kerimcan; Uludamar, Erinc; Tosun, Erdi; Yildizhan, Safak; Aydin, Kadir; Ozcanli, Mustafa
    Replacing conventional diesel fuel has gained great interest owing to environmental issues. Therefore all effect of alternative fuels must be well-known in order to forthcoming engine development concern. In this study acoustic and vibration effect of biodiesel and their blends were investigated on an unmodified diesel engine which enriched with natural gas. Throughout this work, experimental engine was fuelled with conventional diesel, sunflower and canola biodiesel blends with ratio of 20% and 40%, by volume. Furthermore, natural gas was inducted through intake manifold at various flow rates; 5 L/min, 10 L/min, and 15 L/min with intake air. Experiments revealed that, compared to conventional diesel fuel, sunflower and canola biodiesels decreased sound pressure level and vibration of the test engine. Addition of natural gas decreased the values even more. Furthermore, exhaust emission of the engine has been evaluated. Beside experimental study, an artificial neural network model was developed in order to predict sound pressure level and vibration of the engine. Artificial neural network results showed that, generated models were capable of estimation of parameters with high accuracy. (C) 2017 Elsevier Ltd. All rights reserved.
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    Free vibration analysis of functionally graded beams using complementary functions method
    (Springer, 2018) Celebi, Kerimcan; Yarimpabuc, Durmus; Tutuncu, Naki
    A novel approach is employed in the free vibration analysis of simply supported functionally graded beams. Modulus of elasticity, density of material, and Poisson's ratio may change arbitrarily in the thickness direction. The equations of motion are derived using the plane elasticity theory. The governing differential equations have variable coefficients, which are functions of material properties. Analytical solutions of such equations are limited to specific material properties. Hence, numerical approaches must be adopted to solve the problem on hand. The complementary functions method will be infused into the analysis to convert the problem into an initial-value problem which can be solved accurately. Solutions thus obtained are compared to closed-form benchmark solutions available in the literature and finite element software solutions to validate the method presented. Subsequently, it is demonstrated that the method is efficiently applicable to material properties changing arbitrarily through the thickness with continuous derivatives.
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    Investigating the Effect of Weight Reduction of Rod-End in Drag-Link Product with Finite Element Analysis, Fatigue Test, and a Case Study
    (Korean Soc Automotive Engineers-Ksae, 2020) Uludamar, Erinc; Tas, Mustafa; Bicer, Sami Gokberk; Yildirim, Cihan; Yildirim, Ebru Aykut; Celebi, Kerimcan
    The connection surfaces of drag-link must be tough and safe enough to carry transmitted forces that exert on the product in service conditions. Therefore, undulated forming takes place in machining process to stay the rod-ends in the rod. In the rod-end, after forming process, a straight part which remains on the body causes extra cost and weight on the product. In this study, the result of shortening of rod-end which was produced from C45+N quality steel was investigated by comparing with the unmodified rod-end. The comparison was carried out by fatigue test and Finite Element Analysis. The results showed that the cropped part has almost no effect on the durability of the product. It is measured that the modification result with 0,082 kg weight reduction on each rod-end and 5 seconds shortening of machining process were observed by the modification on rod-end. The effect of modification on the part was examined in a case study. The case study indicated that annual expenses of raw material lowered by $9.124,56 and total cost decreased by $11.480,20.
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    Long short-term memory (LSTM) neural network and adaptive neuro-fuzzy inference system (ANFIS) approach in modeling renewable electricity generation forecasting
    (Taylor & Francis Inc, 2021) Bilgili, Mehmet; Yildirim, Alper; Ozbek, Arif; Celebi, Kerimcan; Ekinci, Firat
    Renewable energy sources are developing rapidly worldwide because they are unlimited and permanent, available in every country and also eliminate foreign dependency. In this respect, accurate renewable electricity generation (REG) forecasting is essential in a country's energy planning in relation to its development. In this study, two different data-driven methods such as adaptive neuro-fuzzy inference system (ANFIS) with fuzzy c-means (FCM) and long short-term memory (LSTM) neural network were applied to perform one-day ahead short-term REG forecasting. In addition, short-term hydropower electricity generation (HEG), geothermal electricity generation (GEG), and bioenergy electricity generation (BEG) forecasting were also made using these methods. The correlation coefficient (R), root-mean-square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) were used as evaluation criteria. The values predicted by the ANFIS-FCM and LSTM models were compared with the actual values by evaluating their errors. According to the test results obtained in terms of MAPE evaluation criteria, the best estimation model was obtained for GEG. The lowest MAPE values were found to be 7.20%, 7.46%, 1.63%, and 2.46% for REG, HEG, GEG, and BEG estimates, respectively. The results showed that both ANFIS and LSTM models presented satisfying performances in daily REG prediction, and the ANFIS and LSTM models gave almost identical results.