At present, optimization is an enabling technology in innovation. Multi-objective and multidisciplinary optimization tools are essential in the design process for real-world applications. In turbomaehinery design, these approaches give insight into the design space and identify the tradeoffs between the competing performance measures. This paper describes the application of a novel multi-objective variant of the tabu search algorithm to the aerodynamic design optimization of turbomachinery blades. The aim is to improve the performance of a specific stage and eventually of the whole engine. The integrated system developed for this purpose is described. It combines the optimizer with an existing geometry parameterization scheme and a well-established computational fluid dynamics package. Its performance is illustrated through a case study in which the flow characteristics most important to the overall performance of turbomachinery blades are optimized.@en

Given the focus on incremental change in existing empirical aerodynamic design methods, radical, unintuitive, new optimal solutions in previously unexplored regions of design space are very unlikely to be found using them. We present a framework based on an implicit shape representation and a multiobjective evolutionary algorithm that aims to produce a variety of optimal flow topologies for a given requirement, providing designers with insights into possibly radical solutions. A revolutionary integrated flow simulation system developed specifically for design work is used to evaluate candidate designs.@en

An approach to support the computational aerodynamic design process is presented and demonstrated through the application of a novel multi-objective variant of the Tabu Search optimization algorithm for continuous problems to the aerodynamic design optimization of turbomachinery blades. The aim is to improve the performance of a specific stage and ultimately of the whole engine. The integrated system developed for this purpose is described. This combines the optimizer with an existing geometry parameterization scheme and a well-established CFD package. The system's performance is illustrated through case studies - one two-dimensional, one three-dimensional - in which flow characteristics important to the overall performance of turbomachinery blades are optimized. By showing the designer the trade-off surfaces between the competing objectives, this approach provides considerable insight into the design space under consideration and presents the designer with a range of different Pareto-optimal designs for further consideration. Special emphasis is given to the dimensionality in objective function space of the optimization problem, which seeks designs that perform well for a range of flow performance metrics. The resulting compressor blades achieve their high performance by exploiting complicated physical mechanisms successfully identified through the design process. The system can readily be run on parallel computers, substantially reducing wall-clock run times - a significant benefit when tackling computationally demanding design problems. Overall optimal performance is offered by compromise designs on the Pareto trade- off surface revealed through a true multi-objective design optimization test case. Bearing in mind the continuing rapid advances in computing power and the benefits discussed, this approach brings the adoption of such techniques in real-world engineering design practice a step closer.@en

We present a novel framework for robust aerodynamic design optimization with respect to CFD modeling errors using multi-fidelity simulations, a multi-objective optimization algorithm, and a surrogate model employed to map the error landscape across the design space. We use the low- and high-fidelity CFD model divergence as a proxy for simulation risk, which is simultaneously optimized along with a measure of performance. Instead of generating high-fidelity simulations directly, we employ a Sparse Pseudo-input Gaussian Process surrogate modeling algorithm to predict the divergence. We apply this approach to a simple diffuser design problem, coupled with a multi-objective Tabu Search optimization algorithm, which shows encouraging results. We are able to generate a range of Pareto optimal design, which display a trade-off between aerodynamic performance and simulation risk. This approach is applicable to more general problems and would be of interest in an industrial design setting.

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A method is introduced to improve the conceptual design of turbine blade cooling systems. It delivers greater insights, enables flexibility to explore the design space and provides a more mature start to a conventional design cycle. System representations are rapidly developed using 3-D sketch-based computer models based on idealised, imprecise geometry. Process bottlenecks are eliminated, accelerating design feedback to guide changes. Computational fluid dynamics models provide qualitative coolant flow information. Rapid-prototype models indicate core suitability. An example is presented: coolant flow and core quality are progressively improved and changes made to transform the system style.@en

Aeroengines are designed using fractured processes. Complexity has driven the design of Such machines to be subdivided by specialism, customer and function. While this approach has worked well in the past, with component efficiencies, current material performance, and the possibilities presented by scaling existing designs for future needs becoming progressively exhausted, it is necessary to reverse this process of disintegration. Our research addresses this aim. The strategy we use has two symbiotic arms. The first is an open data architecture from which existing disparate design codes all derive their input and to which all send their output. The second is a dynamic design process management system known as "SignPosting." Both the design codes and parameters are arranged into complementary multiple level hierarchies: fundamental to the successful implementation of our strategy is the robustness of the mechanisms we have developed to ensure consistency in this environment as the design develops over time. One of the key benefits of adopting a hierarchical structure is that it confers not only the ability to use mean-line, throughflow, and fully 3D computational fluid dynamics techniques in the same environment, but also to cross specialism boundaries and to insert mechanical, material, thermal, electrical, and structural codes, enabling, exploration of the design space for multi-disciplinary nonlinear responses to design changes and their exploitation. We present results from trials of an early version of the system applied to the redesign of a generic civil aeroengine core compressor. SignPosting has allowed us to examine the hardness of design constraints across disciplines which has shown that it is far more profitable not to strive for even higher aerodynamic performance, but rather to improve the commercial performance by maintaining design and part-speed pressure ratio stability and efficiency while increasing rotor blade creep life by up to 70%.

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Modern turbofan engines are designed with pressure ratios as high as 40 and with bypass ratios in excess of 8. Multiple spools with substantial radial offset are essential to achieve the desired design and off-design performance and s-shaped ducts are necessary to deliver the flow from the exit of a turbomachine to the inlet of the following one in the minimum possible space to reduce the weight and the size of the gas turbine, without the risk of incurring in flow separation. In the absence of practical design rules or performance correlations for annular s-shaped ducts, a practical design approach could be the use of Computational Fluid Dynamics (CFD) for performance evaluation together with optimisation techniques for seeking the best design. Numerical optimisation methods (either deterministic or stochastic) can be linked to CFD solvers to provide a more thorough exploration of the design space, trying to produce a better design than the datum one, subject to a number of constraints. This paper reports the development and testing of an automatic framework for design optimisation of s-shaped ducts and its initial application to the optimisation of an axial-symmetric inter-compressor duct.

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Process modelling can play an important part in understanding and improving engineering design processes. Meta-data, i.e., numerical information describing the state of a process, can be used to enhance modelling fidelity and to measure predicted behaviour. We explore the application of metadata using a proxy process represented using an Applied Signposting Model. The proxy has been derived from a model of the turbine cooling system design process. We argue that meta-data can be used to control the flow of the modelled process, to couple the behaviour of concurrent sub-processes and to provide quantitative feedback about the process behaviour. We also show that alternative process configurations can be developed to deliver improved performance within the same structure of activities and information flow, and use simulation results to identify such configurations.@en

This paper first reviews the application of design optimization techniques to axial compressor blade design, commenting on the feasibility of this approach for highly constrained, highly dimensional problems. It then analyzes an innovative method to characterize the design space, based on proper orthogonal decomposition (POD). The method was used to generate a reduced order model (ROM) from the true complex system, and revealed its potential to find optimum solutions in selected regions of the design space.

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It is widely accepted that a company's market penetration, and hence its profitability, is very closely linked to the speed with which it can produce a new design. This paper describes a method which aims to assist the designer in producing higher performance turbomachinery designs more quickly by accelerating the process by which they are produced. The adopted approach, based on a recently derived model of the turbomachinery design process, combines an enhanced version of the 'Signposting' design process management methodology with industry-standard analysis codes and CFD, permitting process-wide iteration, near instantaneous generation of guidance data for the designer and fully automatic data handling. A highly successful laboratory experiment based on the design of a large High Pressure Steam Turbine is described and this leads on to current work which incorporates the extension of the proven concept to a full industrial application for the design of Aeroengine Compressors with Rolls-Royce.@en

It is widely acknowledged that a company's ability to aquire market share, and hence its profitability, is very closely linked to the speed with which it can produce a new design. Indeed, a study by the U.K. Department of Trade and Industry has shown that the critical factor which determines profitability is the timely delivery of the new product. Late entry to market or high production costs dramatically reduce profits whilst an overrun on development cost has little significant effect. This paper describes a method which aims to assist the designer in producing higher performance turbomachinery designs more quickly by accelerating the process by which they are produced. The adopted approach combines an enhanced version of the 'Signposting' design process management methodology with industry-standard analysis codes and Computational Fluid Dynamics (CFD). It has been specifically configured to enable process-wide iteration, near instantaneous generation of guidance data for the designer and fully automatic data handling. A successful laboratory experiment based on the design of a large High Pressure Steam Turbine is described and this leads on to current work which incorporates the extension of the proven concept to a full industrial application for the design of Aeroengine Compressors with Rolls-Royce plc.

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