Optimum Design of Turbomachinery Components: A System Based Design

Abstract

Abstract The advent of incredibly fast, increased memory computational systems enable a very systematic design integration of complex engineering modules using an integrated system based approach. Rapid turn-around time for investigating new design concepts is a primary force driving design productivity initiatives across industry. A system based integration focusing on tools for rapid design automation and preliminary design, (e.g. Closed Form Solutions, Response Surfaces, Approximate Numerical Models etc), finite element analysis coupled with optimization methods are needed. Numerical design algorithms (e.g. Sensitivity analysis methods, Feasible Direction methods, Genetic Algorithms, Simulated Annealing, Gradient based Algorithms etc.) at the preliminary and detailed design stages, would ensure higher quality designs from the beginning of the product design cycle. Resulting reliable, robust optimum designs from the preliminary design phase would enable to reduce the overall design cycle time. Large-scale engineering systems (like the gas turbine See Figure. 1) often involve many disciplines which are either loosely or tightly coupled to each other due to the multidisciplinary nature of the interactions. Designers have long recognized the need to decompose such systems into a set of smaller more tractable disciplines. This decomposition is usually based either on engineering disciplines or mathematical models governing the system. Narayan et al. [1] developed a multi-disciplinary design optimization procedure for the design of the aerodynamic shape of turbine blades for enhanced performance using shape optimization techniques. A multidisciplinary design optimization procedure for thin-walled high temperature components has been developed and demonstrated on different components Aerodynamic, heat transfer, structural and modal design objectives are integrated along with various constraint on the blade geometry for multidisciplinary shape optimization. The average blade temperature, maximum blade temperature and the blade weight are minimized with aerodynamic, structural, modal and geometric constraints. A methodology for performing mechanical design of turbine blade components is developed and tested.