Insight into High-quality Aerodynamic Design Spaces through Multi-objective Optimization

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 ste

Multi-Objective Optimisation of Aero-Engine Compressors

The design of a new aero-engine compressor is a complex task: design objectives are almost always conflicting, the design space is large, nonlinear and highly constrained, and the effects of some geometrical changes can be difficult to predict. Computational fluid dynamics (CFD) is now widely used in real-world applications and especially in the design of turbomachinery. However, the large design space and the time required for the numerical simulation of the whole turbomachine make the use of CFD in the early phases of the design process infeasible: preliminary design relies on a number of physical and empirical relations, still quite similar to those used in the early history of turbomachinery design. In this study, 87 independent parameters were used to define the geometry of a 7-stage compressor, the performance of which was evaluated using proprietary design codes for mean-line, multi-stage analysis. The effects on efficiency and surge margin of changing 44 design variables were analysed and their optimal values found by means of deterministic (gradient-based) and meta-heuristic (Tabu Search [TS]) optimisation methods. The results show clearly how the use of meta-heuristic optimisation tools can improve the preliminary design of turbomachinery, allowing a more thorough but still rapid exploration of the design space to identify the most promising regions that will then be verified and further analysed with higher fidelity tools. The results also reveal the impact of introducing various constraints into the design process, highlighting the effects of design decomposition

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

Facilitating the Use of Optimisation in the Aerodynamic Design of Axial Compressors

There is commercial pressure to design axial compressors exhibiting high levels of performance more quickly. This is despite the performance of these machines approaching an asymptote in recent years, with further gains becoming increasingly difficult to achieve. One tool that can be used to help is optimisation, effectively harnessing the speed of computational analysis to accelerate the design process and unlock additional performance improvements. The greatest potential for optimisation exists at the preliminary design stage, however, current methodologies struggle when applied at this early point in the design process due to inadequate problem formulations, an inability to fulfil the role of enhancing designer understanding and a lack of high-fidelity analysis due to computational cost. The goal of this thesis is to facilitate the use of optimisation in the preliminary aerodynamic design of axial compressors by developing an improved methodology that overcomes these limitations. The multiple dominance relations (MDR) formulation enables a larger number of performance parameters to be incorporated in a way that accurately reflects the desires of the designer. This is implemented within a Tabu Search (TS) that is capable of providing interpretable design development information to enhance designer understanding. The combined MDRTS algorithm, overcoming the limitations associated with formulation and understanding, outperforms existing methods when applied to analytic, aerofoil and six-stage axial compressor test cases, generating computational savings of up to 80%. Multi-fidelity techniques are used to accelerate the search by conducting analysis on a "need-to-know'' basis. Computational savings of over 70% are observed compared to the single-fidelity version of the algorithm across the analytic, aerofoil and six-stage axial compressor test cases, enabling high-fidelity analysis to be employed in a computationally efficient manner. The resultant methodology represents a novel and inherently flexible multi-level multi-fidelity optimisation technique. Application to an N-stage axial compressor test case, in which the optimiser is given control over the number of stages in the machine, demonstrates the capabilities of the accelerated MDRTS approach. The complex design space is effectively navigated, generating computational savings of over 90% compared to existing methodologies and producing designs that are more likely to be of interest to the designer. Interpretable design development information is also provided for this problem to enhance designer understanding. These results show that the improved methodology successfully facilitates the use of optimisation in the preliminary aerodynamic design of axial compressors, overcoming the problems associated with formulation, understanding and speed that limit existing approaches

Stochastic axial compressor variable geometry schedule optimisation

The design of axial compressors is dictated by the maximisation of flow efficiency at on design conditions whereas at part speed the requirement for operation stability prevails. Among other stability aids, compressor variable geometry is employed to rise the surge line for the provision of an adequate surge margin. The schedule of the variable vanes is in turn typically obtained from expensive and time consuming rig tests that go through a vast combination of possible settings. The present paper explores the suitability of stochastic approaches to derive the most flow efficient schedule of an axial compressor for a minimum variable user defined value of the surge margin. A genetic algorithm has been purposely developed and its satisfactory performance validated against four representative benchmark functions. The work carries on with the necessary thorough investigation of the impact of the different genetic operators employed on the ability of the algorithm to find the global extremities in an effective and efficient manner. This deems fundamental to guarantee that the algorithm is not trapped in local extremities. The algorithm is then coupled with a compressor performance prediction tool that evaluates each individual's performance through a user defined fitness function. The most flow efficient schedule that conforms to a prescribed surge margin can be obtained thereby fast and inexpensively. Results are produced for a modern eight stage high bypass ratio compressor and compared with experimental data available to the research. The study concludes with the analysis of the existent relationship between surge margin and flow efficiency for the particular compressor under scrutiny. The study concludes with the analysis of the existent relationship between surge margin and flow efficiency for the particular compressor under scrutiny

Super aggressive s-ducts for air breathing rocket engines

Abstract Air breathing rocket engines require turbomachinery and ducting that is substantially lighter than that used in ground based or aerospace gas turbines. In order to reduce the weight of the axial compressor, the design of the inter-spool swan neck duct is targeted. In this paper a circumferential splitter blade is used to reduce loading and diffusion on the duct endwalls. The splitter and duct geometry are coupled and optimised together using 2D CFD. A design is selected that is 30% shorter than ducts that are currently used in aerospace gas turbines and the 3D flow features are investigated in further detail using an experimental rig and 3D CFD. This paper shows that the “splittered” duct has 3 benefits over a conventional duct design: First, separation of the endwalls is prevented even at short duct lengths, this will reduce distortion into the downstream compressor. Second, losses generated by corner separations on structural struts can be reduced by 20%, enabling short ducts to achieve high performance. Third, splittered ducts are shown to be twice as robust to uncertain inlet flow conditions as conventional ducts. This allows a designer to target high performance short designs with reduced risk.</jats:p

Optimization of blade profiles for the Wells turbine

A Wells turbine, when coupled with an oscillating water column, allows the generation of power from the energy in waves on the surface of the ocean. In the present work, a tabu search is used to control the process of optimising the blade profile in the Wells turbine for greater performance, by maximising the torque coefficient. A free form deformation method is used as an efficient means of manipulating the blade profile and computational fluid dynamics in OpenFOAM are used to assess each profile in both two and three dimensions. Investigations into both the flow coefficient at which the optimisation is performed and the number of control variables in the free form deformation tool are performed before optimisations are done on a two-dimensional blade at the hub and tip solidities. This results in increases to the torque coefficient of 34% and 32% at the tip and hub solidities, respectively. These results are then applied to the three-dimensional turbine, giving a 14% increase in the torque coefficient. The results are assessed and an improved method of optimising the blade in two dimensions is proposed.Regione Autonoma Sardegna (grant funding co-authors from University of Cagliari

Multi-objective shape optimisation of a Transonic Fan Rotor downstream of an S-duct

This master's degree thesis aims to optimize a transonic fan following an S-duct through the use of all the tools necessary for an optimization process. In order to perform the required analysis, an automatic CFD based optimization circuit built around GA was built. Specifically, a dedicated parameterization framework was created for 3D blades. In the results it can be seen how the optimization of NASA Rotor 67 gives better results than expected, despite the flow problems created by the S-duc

Impact of Fluid Substitution on the Performance of an Axial Compressor Blade Cascade Working with Supercritical Carbon Dioxide

Abstract Recent research on turbomachinery design and analysis for supercritical carbon dioxide (sCO2) power cycles has relied on computational fluid dynamics. This has produced a large number of works whose approach is mostly case-specific, rather than of general application to sCO2 turbomachinery design. As opposed to such approach, this work explores the aerodynamic performance of compressor blade cascades operating on air and supercritical CO2 with the main objective to evaluate the usual aerodynamic parameters of the cascade for variable boundary conditions and geometries, enabling “full” or “partial” similarity. The results present both the global performance of the cascades and certain features of the local flow (trailing edge and wake). The discussion also highlights the mechanical limitations of the analysis (forces exerted on the blades), which is the main restriction for applying similarity laws to extrapolate the experience gained through decades of work on air turbomachinery to the new working fluid. This approach is a step toward the understanding and appropriate formulation of a multi-objective optimization problem for the design of such turbomachinery components where sCO2 is used as the operating fluid. With this objective, the paper aims to identify and analyze what would be expected if a common description of such computational design problems similar to those where air is the working fluid were used.</jats:p