How to cite this paper
Samani, A. (2018). Combined cycle power plant with indirect dry cooling tower forecasting using artificial neural network.Decision Science Letters , 7(2), 131-142.
References
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Ferretti, G., & Piroddi, L. (2001). Estimation of NOx emissions in thermal power plants using neural networks. Journal of Engineering for Gas Turbines and Power, 123(2), 465-471.
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Liu, C. L., Niu, Y. G., Liu, J. Z., & Jin, X. Z. (2001a). A Boiler Model of 300MW Power Unit for Control System Performance Studies. Acta Simulata Systematica Sinica S, 1.
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Lampart, P., & Yershov, S. (2003). Direct constrained computational fluid dynamics based optimization of three-dimensional blading for the exit stage of a large power steam turbine. Journal of Engineering for Gas Turbines and Power, 125(1), 385-390.
Rich, E., & Knight, K. (1991). Artificial intelligence. 2nd ed. McGraw- Hill, Inc.
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Perryman, R., & Perrott, S. N. (1994, December). Condition monitoring and predictive analysis of combined heat and power systems. In Life Management of Power Plants, 1994., International Conference on (pp. 40-47). IET.
DePold, H. R., & Gass, F. D. (1998, June). The application of expert systems and neural networks to gas turbine prognostics and diagnostics. In ASME 1998 International Gas Turbine and Aeroengine Congress and Exhibition (pp. V005T15A009-V005T15A009). American Society of Mechanical Engineers.
Olausson, P. (2003). On the selection of methods and tools for analysis of heat and power plants. Division of Thermal Power engineering, Lund Institute of Technology, PO Box 118, SE-221 00 LUND, Sweden.
Rahnama, M., Ghorbani, H., & Montazeri, A. (2012, December). Nonlinear identification of a gas turbine system in transient operation mode using neural network. In Thermal Power Plants (CTPP), 2012 4th Conference on (pp. 1-6). IEEE.
Schobeiri, M. T., & Chakka, P. (2002). Prediction of turbine blade heat transfer and aerodynamics using a new unsteady boundary layer transition model. International Journal of Heat and Mass Transfer, 45(4), 815-829.
Tayarani-Bathaie, S. S., Vanini, Z. S., & Khorasani, K. (2014). Dynamic neural network-based fault diagnosis of gas turbine engines. Neurocomputing, 125, 153-165.
Tüfekci, P. (2014). Prediction of full load electrical power output of a base load operated combined cycle power plant using machine learning methods. International Journal of Electrical Power & Energy Systems, 60, 126-140.
Yari, M., Shoorehdeli, M. A., & Yousefi, I. (2013, February). V94. 2 gas turbine identification using neural network. In Robotics and Mechatronics (ICRoM), 2013 First RSI/ISM International Conference on (pp. 523-529). IEEE.
Bassel, W. S., & Gomes, A. V. (2002). A metastable wet steam turbine stage model. Nuclear Engineering and Design, 216(1), 113-119.
Bettocchi, R., Spina, P. R., & Torella, G. (2002, January). Gas Turbine Health Indices Determination by Using Neural Networks. In ASME Turbo Expo 2002: Power for Land, Sea, and Air (pp. 1083-1089). American Society of Mechanical Engineers.
Bhambare, K. S., Mitra, S. K., & Gaitonde, U. N. (2007). Modeling of a coal-fired natural circulation boiler. Journal of Energy Resources Technology, 129(2), 159-167.
Boccaletti, C., Cerri, G., & Seyedan, B. (2000, May). A neural network simulator of a gas turbine with a waste heat recovery section. In ASME Turbo Expo 2000: Power for Land, Sea, and Air (pp. V003T02A008-V003T02A008). American Society of Mechanical Engineers.
Embrechts, M. J., Schweizerhof, A. L., Bushman, M., & Sabatella, M. H. (2000, May). Neural network modeling of turbofan parameters. In ASME Turbo Expo 2000: Power for Land, Sea, and Air (pp. V004T04A008-V004T04A008). American Society of Mechanical Engineers.
Escarela-Perez, R., Arjona-Lopez, M. A., Melgoza-Vazquez, E., Campero-Littlewood, E., & Aviles-Cruz, C. (2004). A comprehensive finite-element model of a turbine-generator infinite-busbar system. Finite Elements in Analysis and Design, 40(5), 485-509.
Ferretti, G., & Piroddi, L. (2001). Estimation of NOx emissions in thermal power plants using neural networks. Journal of Engineering for Gas Turbines and Power, 123(2), 465-471.
Kesgin, U., & Heperkan, H. (2005). Simulation of thermodynamic systems using soft computing techniques. International Journal of Energy Research, 29(7), 581-611.
Kumar, A., Srivastava, A., Banerjee, A., & Goel, A. (2012). Performance based anomaly detection analysis of a gas turbine engine by artificial neural network approach. In Procee. Annual conference of the prognostics and health management society.
Liu, C. L., Niu, Y. G., Liu, J. Z., & Jin, X. Z. (2001a). A Boiler Model of 300MW Power Unit for Control System Performance Studies. Acta Simulata Systematica Sinica S, 1.
Liu, J., Cui, Y., & Jiang, H. (2001b). Investigation of flow in a steam turbine exhaust hood with/without turbine exit conditions simulated. In ASME Turbo Expo 2001: Power for Land, Sea, and Air (pp. V001T03A072-V001T03A072). American Society of Mechanical Engineers.
Lampart, P., & Yershov, S. (2003). Direct constrained computational fluid dynamics based optimization of three-dimensional blading for the exit stage of a large power steam turbine. Journal of Engineering for Gas Turbines and Power, 125(1), 385-390.
Rich, E., & Knight, K. (1991). Artificial intelligence. 2nd ed. McGraw- Hill, Inc.
Russell, S., Norvig, P., & Intelligence, A. (1995). Artificial Intelligence. Prentice-Hall, Egnlewood Cliffs, 25, 27.
Perryman, R., & Perrott, S. N. (1994, December). Condition monitoring and predictive analysis of combined heat and power systems. In Life Management of Power Plants, 1994., International Conference on (pp. 40-47). IET.
DePold, H. R., & Gass, F. D. (1998, June). The application of expert systems and neural networks to gas turbine prognostics and diagnostics. In ASME 1998 International Gas Turbine and Aeroengine Congress and Exhibition (pp. V005T15A009-V005T15A009). American Society of Mechanical Engineers.
Olausson, P. (2003). On the selection of methods and tools for analysis of heat and power plants. Division of Thermal Power engineering, Lund Institute of Technology, PO Box 118, SE-221 00 LUND, Sweden.
Rahnama, M., Ghorbani, H., & Montazeri, A. (2012, December). Nonlinear identification of a gas turbine system in transient operation mode using neural network. In Thermal Power Plants (CTPP), 2012 4th Conference on (pp. 1-6). IEEE.
Schobeiri, M. T., & Chakka, P. (2002). Prediction of turbine blade heat transfer and aerodynamics using a new unsteady boundary layer transition model. International Journal of Heat and Mass Transfer, 45(4), 815-829.
Tayarani-Bathaie, S. S., Vanini, Z. S., & Khorasani, K. (2014). Dynamic neural network-based fault diagnosis of gas turbine engines. Neurocomputing, 125, 153-165.
Tüfekci, P. (2014). Prediction of full load electrical power output of a base load operated combined cycle power plant using machine learning methods. International Journal of Electrical Power & Energy Systems, 60, 126-140.
Yari, M., Shoorehdeli, M. A., & Yousefi, I. (2013, February). V94. 2 gas turbine identification using neural network. In Robotics and Mechatronics (ICRoM), 2013 First RSI/ISM International Conference on (pp. 523-529). IEEE.