Industrial steam turbines are mostly tailor made machinery, varying in a wide range of specifications. This feature introduces high requirements on the design process which has to be flexible, efficient and fast at the same time. Given live steam and design parameters as input, the geometry corresponding to the valid design scheme can be calculated together with the required thermodynamic, aerodynamic and mechanical characteristics. By variation of design parameters a design may be achieved which optimizes both, efficiency and cost. The optimization task is formulated mathematically, e.g. crucial optimization parameters, criteria for evaluation of different designs and other required constraints are selected. The structure of the resulting optimization problem is analyzed. Based on this analysis a modular optimization system design is proposed. The choice of Genetic Algorithms and Adaptive Particle Swarm Optimizer as optimization methods is discussed, recommendations for their proper use are given. A bicriterial optimization approach for a simultaneous optimization of efficiency and cost is developed.
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