Optimization, Genetic Algorithm-based Gas Turbine Engine Cycle

Genetic Algorithms (GA) are new techniques useful for optimization problems, in which the law of 'natural selection' is employed, and it is an evaluating tool to form multi-interpolation in possible solution vectors. The advantages in convergence, structures, no requirements to the optimization function and so on can enable it to be effectively applied in the design of the engine.The task of this thesis contains: The computational programs of normal GA, and their relevant improvement according to the requirement of computational efficiency; From these computations, many genetic arithmetic operators in different genetic algorithms is used to validate their influence on the results, thus it supplies a set of parameters that are fit for the cycle analysis of the engine;On this basis, the control module of optimization design is established, the method that the modules of GA and the inputs, outputs, executive files of engine cycle analysis are applied is used to solve generalized problems in the cycle analysis calculation of different engines. At the same time, it can extend the calculation (other calculations added) and expand the optimization problems (dimension, weight design, airplane/engine incorporated design) in the design of the engine, thus it has the simple frame of generalization optimization software.Finally, the optimization results of the cycle parameters for one engine design point are followed, and the results with optimization are compared with those without optimization, and the former are better than the latter.