- About this Journal
- Abstracting and Indexing
- Aims and Scope
- Article Processing Charges
- Articles in Press
- Author Guidelines
- Bibliographic Information
- Citations to this Journal
- Contact Information
- Editorial Board
- Editorial Workflow
- Free eTOC Alerts
- Publication Ethics
- Reviewers Acknowledgment
- Submit a Manuscript
- Subscription Information
- Table of Contents
Advances in Artificial Intelligence
Volume 2012 (2012), Article ID 610487, 7 pages
Radial-Basis-Function-Network-Based Prediction of Performance and Emission Characteristics in a Bio Diesel Engine Run on WCO Ester
1Department of Mechanical Engineering, MIT, Manipal 576104, India
2Department of Mechanical Engineering, NMAMIT, Nitte 574110, India
Received 12 May 2012; Accepted 21 September 2012
Academic Editor: Jun He
Copyright © 2012 Shiva Kumar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- J. Huang, Y. Wang, S. Li, A. P. Roskilly, H. Yu, and H. Li, “Experimental investigation on the performance and emissions of a diesel engine fuelled with ethanol-diesel blends,” Applied Thermal Engineering, vol. 29, no. 11-12, pp. 2484–2490, 2009.
- K. Sureshkumar, R. Velraj, and R. Ganesan, “Performance and exhaust emission characteristics of a CI engine fueled with Pongamia pinnata methyl ester (PPME) and its blends with diesel,” Renewable Energy, vol. 33, no. 10, pp. 2294–2302, 2008.
- A. K. Agarwal and K. Rajamanoharan, “Experimental investigations of performance and emissions of Karanja oil and its blends in a single cylinder agricultural diesel engine,” Applied Energy, vol. 86, no. 1, pp. 106–112, 2009.
- T. Venkateshwara Rao, G. Prabhakar Rao, and K. Hema Chandra Reddy, “Experimental investigation of pongamia, Jatropa, Neem metyl esters as biodiesel in C.I. Engine,” Jordan Journal of Mechanical and Industrial Engineering, vol. 2, no. 2, pp. 117–122, 2008.
- A. P. Roskilly, S. K. Nanda, Y. D. Wang, and J. Chirkowski, “The performance and the gaseous emissions of two small marine craft diesel engines fuelled with biodiesel,” Applied Thermal Engineering, vol. 28, no. 8-9, pp. 872–880, 2008.
- A. K. Hossain and P. A. Davies, “Plant oils as fuels for compression ignition engines: a technical review and life-cycle analysis,” Renewable Energy, vol. 35, no. 1, pp. 1–13, 2010.
- A. K. Babu and G. Devaradjane, “Vegetable oils and their derivatives as fuel for CI engines—an overview,” SAE Technical Paper 2003-01-0767, SAE International.
- A. S. Ramadhas, S. Jayaraj, and C. Muraleedharan, “Use of vegetable oils as I.C. Engine fuels—a review,” Renewable Energy, vol. 29, no. 5, pp. 727–742, 2004.
- S. Zheng, M. Kates, M. A. Dubé, and D. D. McLean, “Acid-catalyzed production of biodiesel from waste frying oil,” Biomass and Bioenergy, vol. 30, no. 3, pp. 267–272, 2006.
- A. V. Tomasevic and S. S. Siler-Marinkovic, “Methanolysis of used frying oil,” Fuel Processing Technology, vol. 81, no. 1, pp. 1–6, 2003.
- M. Canakci and A. Necati Özsezen, “Evaluating waste cooking oils as alternative diesel fuel,” Gazi University Journal of Science, vol. 18, no. 1, pp. 81–91, 2005.
- Z. Utlu and M. S. Koçak, “The effect of biodiesel fuel obtained from waste frying oil on direct injection diesel engine performance and exhaust emissions,” Renewable Energy, vol. 33, no. 8, pp. 1936–1941, 2008.
- M. L. Traver and R. J. Atkinson, “Neural network based diesel engine emission prediction using in cylinder combustion pressure,” SAE Technical Paper 1999-01-1532, SAE International.
- D. Yuanwang, Z. Meilin, X. Dong, and C. Xiaobei, “An analysis for effect of cetane number on exhaust emissions from engine with the neural network,” Fuel, vol. 81, no. 15, pp. 1963–1970, 2002.
- M. Gölcü, Y. Sekmen, P. Erduranli, and M. S. Salman, “Artificial neural-network based modeling of variable valve-timing in a spark-ignition engine,” Applied Energy, vol. 81, no. 2, pp. 187–197, 2005.
- M. M. Prieto, E. Montanes, and O. Menendez, “Power plant condenser performance forecasting using a non-fully connected artificial neural network,” Energy, vol. 26, no. 1, pp. 65–79, 2001.
- H. Bechtler, M. W. Browne, P. K. Bansal, and V. Kecman, “Neural networks—a new approach to model vapour-compression heat pumps,” International Journal of Energy Research, vol. 25, no. 7, pp. 591–599, 2001.
- J. M. Alonso, F. Alvarruiz, J. M. Desantes, L. Hernández, V. Hernández, and G. Moltó, “Combining neural networks and genetic algorithms to predict and reduce diesel engine emissions,” IEEE Transactions on Evolutionary Computation, vol. 11, no. 1, pp. 46–55, 2007.
- B. Ghobadian, H. Rahimi, A. M. Nikbakht, G. Najafi, and T. F. Yusaf, “Diesel engine performance and exhaust emission analysis using waste cooking biodiesel fuel with an artificial neural network,” Renewable Energy, vol. 34, no. 4, pp. 976–982, 2009.
- T. F. Yusaf, D. R. Buttsworth, K. H. Saleh, and B. F. Yousif, “CNG-diesel engine performance and exhaust emission analysis with the aid of artificial neural network,” Applied Energy, vol. 87, no. 5, pp. 1661–1669, 2010.
- C. Sayin, H. M. Ertunc, M. Hosoz, I. Kilicaslan, and M. Canakci, “Performance and exhaust emissions of a gasoline engine using artificial neural network,” Applied Thermal Engineering, vol. 27, no. 1, pp. 46–54, 2007.
- E. Arcaklioǧlu and I. Çelikten, “A diesel engine's performance and exhaust emissions,” Applied Energy, vol. 80, no. 1, pp. 11–22, 2005.
- Z. T. Liu and S. M. Fei, “Study of CNG/diesel dual fuel engine's emissions by means of RBF neural network,” Journal of Zhejiang University, vol. 5, no. 8, pp. 960–965, 2004.
- R. Johnsson, “Cylinder pressure reconstruction based on complex radial basis function networks from vibration and speed signals,” Mechanical Systems and Signal Processing, vol. 20, no. 8, pp. 1923–1940, 2006.
- K. K. Botros, G. Kibrya, and A. Glover, “A demonstration artificial neural-networks-based data mining for gas-turbine-driven compressor stations,” Journal of Engineering for Gas Turbines and Power, vol. 124, no. 2, pp. 284–297, 2002.
- N. Roy and R. Ganguli, “Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring,” Applied Soft Computing, vol. 6, no. 2, pp. 154–169, 2006.
- S. Haykin, Neural Networks, A Comprehensive Foundation, Macmillan, New York, NY, USA, 1984.
- P. Srinivasa Pai, T. N. Nagabhushan, P. K. Ramakrishna Rao, et al., “Radial basis function neural networks for tool wear monitoring,” International Journal of COMADEM, vol. 5, no. 3, pp. 21–30, 2003.
- P. Srinivasa Pai, Acoustic emission based tool wear monitoring using some improved neural network methodologies [Ph.D. thesis], S.J. College of Engineering, University of Mysore, Mysore, India, 2004.