Robust design optimization of gas turbine compression systems

Gas turbine compression systems are required to perform adequately over a range of operating conditions. Complexity has encouraged the conventional design process for compressors to focus initially on one operating point, usually the most commonor arduous, to draw up an outline design. Generally, only as this initial design is refined is its offdesign performance assessed in detail. Not only does this necessarily introduce a potentially costly and timeconsuming extra loop in the design process, but it also may result in a design whose offdesign behavior is suboptimal. Aversion of nonintrusive polynomial chaos was previously developed in which a set of orthonormal polynomials was generated to facilitate a rapid analysis of robustness in the presence of generic uncertainties with good accuracy. In this paper, this analysis method is incorporated in real time into the design process for the compression system of a three-shaft gas turbine aeroengine. This approach to robust optimization is shown to lead to designs that exhibit consistently improved system performance with reduced sensitivity to offdesign operation.

Tailored seeding geometries for the multi-fidelity design of compression systems

Design optimisation of compressor systems is a computationally expensive problem due to the large number of variables, complicated design space and expense of the analysis tools. One approach to reduce the expense of the process and make it achievable in industrial timescales is to employ multi-fidelity techniques, which utilise more rapid tools in conjunction with the highest fidelity analyses. The complexity of the compressor design landscape is such that the starting point for these optimisations can influence the achievable results; these starting points are often existing (optimised) compressor designs, which form a limited set in terms of both quantity and diversity of the design. To facilitate the multi-fidelity optimisation procedure, a compressor synthesis code was developed which allowed the performance attributes (e.g. stage loadings, inlet conditions) to be stipulated, enabling the generation of a variety of compressors covering a range of both design topology and quality to act as seeding geometries for the optimisation procedures. Analysis of the performance of the multi-fidelity optimisation system when restricting its exploration space to topologically different areas of the design space indicated little advantage over allowing the system to search the design space itself. However, comparing results from optimisations started from seed designs with different aerodynamic qualites indicated an improved performance could be achieved by starting an optimisation from a higher quality point, and thus that the choice of starting point did affect the final outcome of the optimisations. Both investigations indicated that the performance gains through the optimisation were largely defined by the early exploration of the design space where the multi-fidelity speedup could be exploited, thus extending this region is likely to have the greatest effect on performance of the optimisation system. © 2013 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

Tailored seeding geometries for the multi-fidelity design of compression systems

Design optimisation of compressor systems is a computationally expensive problem due to the large number of variables, complicated design space and expense of the analysis tools. One approach to reduce the expense of the process and make it achievable in industrial timescales is to employ multi-fidelity techniques, which utilise more rapid tools in conjunction with the highest fidelity analyses. The complexity of the compressor design landscape is such that the starting point for these optimisations can influence the achievable results; these starting points are often existing (optimised) compressor designs, which form a limited set in terms of both quantity and diversity of the design. To facilitate the multi-fidelity optimisation procedure, a compressor synthesis code was developed which allowed the performance attributes (e.g. stage loadings, inlet conditions) to be stipulated, enabling the generation of a variety of compressors covering a range of both design topology and quality to act as seeding geometries for the optimisation procedures. Analysis of the performance of the multi-fidelity optimisation system when restricting its exploration space to topologically different areas of the design space indicated little advantage over allowing the system to search the design space itself. However, comparing results from optimisations started from seed designs with different aerodynamic qualites indicated an improved performance could be achieved by starting an optimisation from a higher quality point, and thus that the choice of starting point did affect the final outcome of the optimisations. Both investigations indicated that the performance gains through the optimisation were largely defined by the early exploration of the design space where the multi-fidelity speedup could be exploited, thus extending this region is likely to have the greatest effect on performance of the optimisation system. © 2012 AIAA.

An investigation of higher-order multi-objective optimisation for 3D aerodynamic shape design

We investigate the performance of different variants of a suitably tailored Tabu Search optimisation algorithm on a higher-order design problem. We consider four objective func- tions to describe the performance of a compressor stator row, subject to a number of equality and inequality constraints. The same design problem has been previously in- vestigated through single-, bi- and three-objective optimisation studies. However, in this study we explore the capabilities of enhanced variants of our Multi-objective Tabu Search (MOTS) optimisation algorithm in the context of detailed 3D aerodynamic shape design. It is shown that with these enhancements to the local search of the MOTS algorithm we can achieve a rapid exploration of complicated design spaces, but there is a trade-off be- tween speed and the quality of the trade-off surface found. Rapidly explored design spaces reveal the extremes of the objective functions, but the compromise optimum areas are not very well explored. However, there are ways to adapt the behaviour of the optimiser and maintain both a very efficient rate of progress towards the global optimum Pareto front and a healthy number of design configurations lying on the trade-off surface and exploring the compromise optimum regions. These compromise solutions almost always represent the best qualitative balance between the objectives under consideration. Such enhancements to the effectiveness of design space exploration make engineering design optimisation with multiple objectives and robustness criteria ever more practicable and attractive for modern advanced engineering design. Finally, new research questions are addressed that highlight the trade-offs between intelligence in optimisation algorithms and acquisition of qualita- tive information through computational engineering design processes that reveal patterns and relations between design parameters and objective functions, but also speed versus optimum quality. © 2012 AIAA.