This paper presents an Artificial Neural Network (ANN) - based modeling technique for prediction of outlet temperature, pressure and mass flow rate of gas turbine combustor. ANN technique has been developed and used to model temperature, pressure and mass flow rate as a nonlinear function of fuel flow rate to the combustion chamber. Results obtained by present modeling are compared with those obtained by experiment. A quantitative analysis of modeling technique has been carried out using different evaluation indices; namely, Mean-Square-Quantization-Error (MSQE) and actual percentage error. The results show the effectiveness and capability of the proposed modeling technique with reasonable accuracies of about 95 percent.
Modeling of Gas Turbine Combustor Using Dynamic Neural Network
- Views Icon Views
- Share Icon Share
- Search Site
Lahroodi, M, & Mozafari, AA. "Modeling of Gas Turbine Combustor Using Dynamic Neural Network." Proceedings of the ASME 2006 International Mechanical Engineering Congress and Exposition. Dynamic Systems and Control, Parts A and B. Chicago, Illinois, USA. November 5–10, 2006. pp. 1229-1235. ASME. https://doi.org/10.1115/IMECE2006-15737
Download citation file: