The optimisation of steam turbine design

Abstract

The world market-place for steam turbine products is becoming increasingly competitive, and manufacturers must routinely produce designs which are extensively optimised whilst working within demanding tender and contract lead-times. The objective of the research work has been to develop a methodology whereby established turbomachinery analysis methods can be integrated within a framework of optimising algorithms. A rule-base, numerical optimisation, fuzzy logic, and genetic algorithms are used to optimise bladepath configurations, with particular emphasis on the minimisation of life-cycle operating costs. Significantly, automation of the design process is increased, design lead-times can be reduced, and performance improvements are predicted. The optimisation procedure relies on a sequential approach, with much emphasis placed on the iterative running of simple design codes. Simplified design methods are often reliant on correlated loss data to predict turbine performance, and in some cases this data is inaccurate or incomplete. An example of this is in the design of partially-admitted control stages, where little published data is available. It is suggested that CFD methods can, in some cases, be applied to derive new performance correlations or re-assess the validity of existing models. The application of an unsteady CFD solver to typical control stage geometries is presented in detail, and the approach is extended to include the development of a new control stage optimisation method.