DocumentCode :
2891393
Title :
Use Fuzzy Neural Network to Model Gas Turbine Cooled Blades
Author :
Wang, Tong ; He, Pi-Lian ; Pashayev, A.
Author_Institution :
Comput. Sci. & Technol. Coll., Tianjin Univ.
fYear :
2006
fDate :
13-16 Aug. 2006
Firstpage :
1829
Lastpage :
1835
Abstract :
In this paper, the mathematical models and high effective combination numerical methods for calculating of stationary and dynamic temperature field of a profile part of a blade with convective cooling are put forward. The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging integral processes have been developed and the estimations of errors in the terms of Karnel continuity modules have been received. Boundary conditions of heat exchange are determined by the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigation heat and hydraulic characteristics of the gas turbine
Keywords :
aerospace engines; blades; convection; cooling; error analysis; estimation theory; fuzzy neural nets; gas turbines; integral equations; mechanical engineering computing; Karnel continuity module; boundary condition; convective cooling; dynamic temperature; error estimation; fuzzy neural network; gas turbine cooled blade; heat exchange; integral equation; mathematical model; numerical method; splines; stationary temperature; Blades; Boundary conditions; Conducting materials; Cooling; Cybernetics; Educational institutions; Fuzzy neural networks; Machine learning; Mathematical model; Shape; Temperature dependence; Temperature distribution; Turbines; Boundary temperature calculation; gas turbine blade; neural networks; splines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
Type :
conf
DOI :
10.1109/ICMLC.2006.259045
Filename :
4028362
Link To Document :
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