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Multidisciplinary Adjoint Design Optimisation of Gasturbines

Periodic Reporting for period 1 - MADDOG (Multidisciplinary Adjoint Design Optimisation of Gasturbines)

Reporting period: 2015-09-01 to 2017-08-31

Optimisation techniques are increasingly being adopted in industrial design processes, where more and more components are designed through significant use of computational analysis. This is the logic consequence of the increased capacity of numerical modelling techniques to accurately predict the behaviour and performance of the components. Through optimisation techniques, these numerical models are automatically and systematically explored to modify designs such that their performance improves, quite often beating designs developed by skilled engineers while obtained in a much shorter timeframe.
One of the most promising techniques to improve designs is based on sensitivity analysis, which tells how much impact a certain design change will have on performance. These sensitivities can be computed efficiently using the adjoint approach, for which the computational cost is independent from the number of design variables, and thus allows to explore a very rich design space. Through the adjoint approach, the optimisation of very complex machines such as full gas turbines is within reach of the current computational capacity. This would have a significant environmental impact as the efficiency of many energy conversion systems on which we rely today can be substantially improved through advanced use of optimisation techniques. The current situation is however far from this prospect, as still major advancements are needed in adjoint methods.
This project has tackled two major shortcomings, which are perceived as the major bottleneck of application of adjoint methods in industrial use. The first issue relates to the parametrisation of the shape optimisation problem. The current practice is to optimise a discrete shape model, such that the optimal shape is represented by a cloud of points rather than a collection of smooth analytically described surfaces, which is the current industrial practice. Hence, a post-processing step is required to fit the point cloud by smooth surfaces, impairing optimality. In this project, the shape has been considered from the start as described by a geometric model which is guaranteed to have smooth surfaces.
A second issue with respect to current shape optimisation practices is that only single disciplines are considered at once. In many applications, only the fluid problem is considered, and the shape is optimised to reach better aerodynamic performance. In general, the resulting shape will not meet structural requirements and hence needs to be reshaped, adding significantly to the design effort while failing to find a compromise solution. In this work, different disciplines are considered simultaneously.
The aim of this project was to develop a multidisciplinary framework for the optimisation of turbomachinery blades such that significant improvements in aerodynamic performance could be achieved while keeping structural requirements satisfied.
To achieve this goal, an open-source structural solver was differentiated such that sensitivities of the mechanical stresses with respect to shape changes could be determined efficiently. Next to this, a Computer Aided Design (CAD) kernel was differentiated allowing to describe the blade shapes using standard industrial practices and enabling the computation of sensitivities through this process.
The developed tools were illustrated on an industrial test case. A radial turbine wheel, used in turbochargers of passenger cars, was aerodynamically optimised while keeping the stresses limited to a predefined limit. An improvement of 6% in efficiency was achieved while lowering the structural loads on the blades. The total design time was significantly reduced from several weeks to only 9 days.
Additionally a novel parametrisation method for the volume was developed during the project by considering tri-variate b-spline volumes. The method was applied to the design of a u-bend return channel, where a 60% reduction in pressure losses was obtained.
The results of this work have been presented a several conferences and have drawn the attention of different industrial stakeholders. The research has initiated a collaboration with automotive industry with a follow-up project.
This project demonstrated the validity of the proposed approach which has significant benefits for industry:
-) existing products can be significantly improved in a reduced time and effort,
-) the concurrent approach, considering both aero-performance and structural requirements, allows to reach better compromises between both disciplines, leading to increased efficiencies without compromising on reliability,
-) optimisation of large and complex systems is now within reach. Significant further improvements in efficiencies are expected through optimising the interactions between multiple components, so far been out of reach.
The demonstrator opens the road further to implement more disciplines into the framework.
Entropy in optimized radial turbine