iosr-JMCE   Volume-9 ~ Issue-2

Paper Type	:	Research Paper
Title	:	Effect of Pilot Fuel Quantity on the Performance and Emission Characteristics of a Pre-Mixed CNG - Diesel Dual Fuel Mode Engine
Country	:	India
Authors	:	K. Suresh Kumar, Dr. B. Sudheer Premkumar, Dr. K. Rajagopal, Dr. V.S.S. Murthy, Dr. Srinivasa Rao, C. NagaRaja
	:	10.9790/1684-0920109

Abstract: The serious environmental pollution and the energy crisis all over the world has caused for development of the lower pollution and lower energy consumption automobile to become major research goal. With huge back ground, Compressed Natural Gas (CNG) is projected as the best alternative fuel for the country like India. The properties of CNG make it an ideal fuel for direct use in spark ignition engines. Conversion of any existing spark ignition engine to operate on natural gas is relatively simple with available equipment. Many spark ignition engine vehicles are successfully operating in major cities of India with CNG fuel. However CNG cannot be used as a fuel in diesel engines with ease. Since the maximum engines at present run on diesel, it will be very much useful if a solution could be found to alter the existing diesel engine with minimum modifications to run on CNG. Several researchers could attempt to run diesel engines with CNG. In the process three methods were reported to be successful to use CNG as a fuel in diesel engines, they are (i) Spark ignited gas mode (ii) Direct injection of CNG in dual fuel mode and (iii) Premixed CNG dual fuel mode. In the present work a premixed dual fuel engine was developed which can perform well for the entire range of load and experiments are carried out by varying the pilot fuel amount and studied the effect of pilot fuel amount on engine performance and emissions characteristics and determined optimum fuel injection quantity for better performance and lower emissions.

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Paper Type	:	Research Paper
Title	:	The Performance Analysis of a Fettling Shop Using Simulation
Country	:	India
Authors	:	Mathew Thomas
	:	10.9790/1684-0921014

Abstract: Fettling shop is the product finishing shop of casting products.After the knockout, the casting is taken to the fettling shop for doing the fettling work. The fettling process includes cutting, shot blasting, grinding and painting. In all these process the sand and extra metal on the castings are removed. The project titled "The performance analysis of a fettling shop using simulation‟ is based on a fettling shop of a casting industry. The main aim of the project is the performance analysis of the fettling shop. This project is a simulation based project and is done using a simulation tool called arena. The main concepts related with the performance analysis are Bottleneck analysis, Productivity analysis and System improvement analysis.

Keywords: Performance analysis, Fettling shop, Bottleneck, Simulation.

[1] Al.Araidah, O.Boran (2012) -"Reducing delay in healthcare delivery at outpatients clinics using discrete event simulation".

[2] Bronislav Chramcov, Petr beran (2005) -"A simulation approach to achieving more efficient production systems".

[3] Chompoonoot kasemset,Voratas kachitvichyanukul (2008)- "Simulation-based procedure for implementing theory of constraints: extension for cases with multiple bottlenecks".

[4] Christoph Roser,Masaru Nakano ,Minoru Tanaka (2002) –"Shifting bottleneck detection".

[5] Felipe f. Baesler,Milton Moraga,Francisco j. Ramis (2002) -"Productivity improvement in the wood industry using simulation and artificial intelligence".

[6] Galina Merkuryeva (2005) –"Metamodelling for simulation applications in production".

[7] Julian h. Kang,Sung-mo ahn , Ji-hyun nam (2006)-"Productivity assessment of rock transportation trucks using simulation technology".

[8] Kidak Levent B,Aksarayli Mehmet (2011) -"Simulation modeling for process improvement in a general surgery service".

[9] Melaka (2009)-"Productivity analysis of table top fan assembly process using arena simulation".

[10] Navin Gupta, Edward j. Williams (2005) –"Simulation improves service and profitability of an automobile service garage".

Paper Type	:	Research Paper
Title	:	Design and Optimization of Forged aluminium Tension strut
Country	:	India
Authors	:	M. Rachel Roshiny, K. Devaki Devi
	:	10.9790/1684-0921521

Abstract:Suspension system of an automobile plays an important role in ensuring the stability of the automobile. Although it has been achieved to a considerable extent, another major aspect of suspension system is passenger car. Now a day in automobile Industries every supplier is trying to give a good product with cheap price to the customer. By considering the customer requirement I am designing Forged aluminium Tension Strut which will satisfy the customer requirement. Tension Strut is the part of Linkages system which is link between the Chassis and Wheel assembly with specific ball joint at one side and Bushing at another side. In SUV (sport utility vehicle) the strength requirement of tension strut is always in higher demand and shape should not be more bulge. Due to this requirement most of the suppliers are prefer to use "Steel" material for forged tension strut. In this project I am designing the Tension strut in 3D software Catia V-5 by providing the different types of shapes or Sections and will optimize the 3D model in FEA by applying the aluminium material for Static Load cases.FEA in V-5 will give 90% - 95% accuracy of result but it will take very less time as compare to other FEA software.

Keyword: Aluminium forging,CAD-Catia V-5,Finite Element Analysis-Catia V-5.

[1]. http://forums.tccoa.com/showthread.php?t=124547
[2]. http://www.custommagnums.com/forums/engine-performance-mods/40365-how-replace-tension-struts.html
[3]. http://www.alu-stock.es/en/technical/information.html
[4]. http://www.witzenmann.in/download/Manual%20of%20metal%20bellows_0441e%20S%20174-199_2_04_10_20_web.pdf
[5]. http://www.grantadesign.com/education/datasheets/sciencenote.htm

Paper Type	:	Research Paper
Title	:	Shear Stress Prediction Using FEA-ANN Hybrid Modeling Of Eicher 11.10 Chassis Frame
Country	:	India
Authors	:	Tushar M. Patel, Dr. N. M. Bhatt
	:	10.9790/1684-0922232

Abstract: The chassis serves as a backbone for supporting the body and different parts of the automobile. It should be rigid enough to withstand the shock, twist, vibration and other stresses. Along with strength (Shear Stress), an important consideration in chassis design is to have adequate bending stiffness (Deflection). The main objective of the research is to develop an ANN model for shear stress prediction. The chassis frame is made of two side members joined with a series of cross members. The number of cross members, their locations, cross-section and the sizes of the side and the cross members becomes the design variables. The chassis frame model is to be developed in Solid works and analyzed using Ansys. Since the no. of parameters and levels are more, the probable models are too many. The weight reduction of the sidebar is achieved by changing the Parameters using the orthogonal array. Then FEA is performed on those models. ANN model is prepared using the results of FEA. For the ANN modeling, the standard back-propagation algorithm is found to be the best choice for training the model. A multi- layer perception network is used for non-linear mapping between the input and output parameters. This model can save material used, production cost and time.

Keywords: Optimization, Chassis frame, FE analysis, FEA-ANN hybrid modeling, Weight reduction

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[2]. Javadi, A. A., Tan, T. P., & Zhang, M. (2003). Neural network for constitutive modelling in finite element analysis. Computer Assisted Mechanics and Engineering Sciences, 10 (4), 523-530.

[3]. Spina, R. (2006). Optimization of injection moulded parts by using ANN-PSO approach. Journal of Achievements in Materials and Manufacturing Engineering,15 (1-2), 146-152.

[4]. Saltan, M., & Sezgin, H. (2007). Hybrid neural network and finite element modeling of sub-base layer material properties in flexible pavements. Materials & design, 28(5), 1725-1730.

[5]. Benardos, P. G., & Vosniakos, G. C. (2007). Optimizing feedforward artificial neural network architecture. Engineering Applications of Artificial Intelligence, 20 (3), 365-382.

[6]. Cardozo, S. D., Gomes, H., & Awruch, A. (2011). Optimization of laminated composite plates and shells using genetic algorithms, neural networks and finite elements. Latin American Journal of Solids and Structures, 8 (4), 413-427.