The Impacts of Ethanol - Gasoline Blended Fuels on the Pollutant Emissions and Performance of a Spark -Ignition Engine: An Empirical Study

[Ümit Ağbulut, Suat Sarıdemir, Gökhan Durucan] Volume 5: Issue 4, December 2018, pp 50-59 

DOI: 10.26706/IJAEFEA.4.5.20181201

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Abstract - The blending of ethanol with imported gasoline types has been compulsory since January 1, 2018, with the Communiqué No. 30098 published in the Official Gazette in Turkey. In line with this, it is aimed to determine the effects of gasoline-ethanol blends on engine performance and exhaust emissions resulting from the use of an SI engine. The experiments were performed at different speeds for different ethanol-gasoline blends (E0, E10 and E20) under full load in a four-stroke, single-cylinder engine. As a result, air-fuel mixture ratios, torque, power, vibration and noise values, specific fuel consumption, harmful gas emissions (CO, HC, CO2 and NOx) was measured. Measurements were obtained with 96% accuracy. In this study, carbon monoxide and hydrocarbon emissions decreased, carbon dioxide and nitrogen oxide emissions increased by the addition of ethanol to gasoline. On the other hand, the addition of ethanol has also led to a certain increase in brake specific fuel consumption, vibration and noise levels.

Index terms - Engine performance, Ethanol-gasoline blends, Exhaust emission, Fossil fuels.
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Optimization of Cutting Parameters in Finishing Milling of Hardox 400 Steel

[Fuat KARA] Volume 5: Issue 3, October 2018, pp 44-49 

DOI: 10.26706/IJAEFEA.3.5.20180901

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Abstract - In this study, it was performed to optimization of cutting parameters in finishing milling of Hardox 400 steel with PVD TiAlN+TiN coated carbide inserts. Milling experiments were made according to Taguchi L16 orthogonal array. The evaluation of the experimental results was based on the signal/noise (S/N) ratio. Control factors that given optimum surface roughness values were determined by using the Taguchi method. Two different cutting speeds (60 and 120 m/min) and cooling method (dry and wet) as control factors was selected. In addition, depth of cut and feed rate were taken as 0.3 mm and 0.1 mm/rev, respectively. The effect levels on the surface roughness of the control factors with analysis of variance (ANOVA) performed using the experimental results were determined. The Taguchi analysis found the optimum results for surface roughness to be with the cutting speed of 120 m/min and cooling method of wet.

Index terms - Finishing milling, Hardox 400, Taguchi method, surface roughness
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[6] F. Kara, ―Optimization of surface roughness in finish milling of AISI P20+ S plastic-mold steel,‖ Mater Technol., vol. 52(2), pp. 195–200, 2018.

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[9] F. Kara and B. Öztürk, ―Comparison and optimization of PVD and CVD method on surface roughness and flank wear in hard-machining of DIN 1.2738 mold steel,‖Sensor Rev.,https://doi.org/10.1108/SR-12-2017-0266, in press, 2019.

[10] E. Yücel and M. Günay, ―Modelling and optimization of the cutting conditions in hard turning of high-alloy white cast iron (Ni-Hard),‖Proc Inst MechEng Part C: J MechEng Sci.,vol. 227(10), pp. 2280-2290, 2013.

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[12] E. Yücel and H. Saruhan,―Design optimization of rotor-bearing system considering critical speed using Taguchi method,‖Proceedings of the Institution of Mechanical Engineers, Part E: J Process Mech Eng., vol. 231(2), pp. 138-146, 2017.
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Investigation of Electric Field Distribution of A Transformer Using Moving Finite Element Method

[Mehmet ÇINARİrfan ÖKTEN] Volume 5: Issue 2, June 2018, pp 36-43 

DOI: 10.26706/IJAEFEA.2.5.20180602

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Abstract - The one of the commonly used methods for solution of partial differential equations is the finite element method. Solution area for the differential equation to be solved in this method; are divided into a number of sub-regions called simple , small , interconnected , finite elements.However , especially in time-dependent partial differential equations, analysis is performed using the moving finite element method instead of the classical finite element method where the solution network changes locally; both faster and more accurate.In this work, moving finite element method is considered. The details of how the original variation on the solution network for he moving finite element method and the monitor function selection, which is an important factor in these changes, are detailed in the two-dimensional case. As application, C ++ based software is implemented and analyzed the transformer’s electric area distribution according to the state of the classical and moving finite elements and the results are compared.
Index terms - Mesh Generation , Finite Element Method, Moving Finite Element
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REFERENCES
[1] Mehmet Aydın, Beno Kuryel, Gönül Gündüz, Galip Oturanç, 2001,” Diferansiyel Denklemler ve Uygulamaları”,İzmir.

[2] Thomas R. Hughes , 2000, “The Finite Element Method Linear Static and Dynamic Finite Element Method”, Dover Publications, New York

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[6] Weiming Cao, Weizhang Huang, Robert D. Rusell, 1998, ”An r-Adaptive Finite Element Method Based Upon Moving Mesh PDEs” ,Journal of Computational Physiscs, 149, pp: 221-244.

[7] Weiming Cao, Weizhang Huang, Robert D. Rusell, 1998, ”An r-Adaptive Finite Element Method Based Upon Moving Mesh PDEs” ,Journal of Computational Physiscs, 149, pp: 221-244.

[8] Weiming Cao, Weizhang Huang, Robert D. Rusell,1994, “A Study Of Monitor Functions For Two-Dıemensional Adaptive Mesh Generation”, SIAM J. SCI.Computer, Vol:20 No: 6, pp: 1978-1994.

[9] Miller K, Miller R.N, 1981, “Moving Finite Elements:Part 1”, SIAM J.Numer Anal 18: 1019-1052.

[10] Jimack P,1988 a, “High order moving finite elements II”, Report number AM-88-03 School of Mahtematics,University of Bristol,U.K

[11] Johnson, I.W,Wathen, A., Baines, M.J (1988) Moving Finite Elements for Evolutionary Problems(II) Applications. J.Comput. PHYS. 79 pp 270-297.
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