The tolerance of a turbine blade aerofoil is determined by the requirements to achieve an aerodynamic performance in operation. In fact, the manufacturing tolerance applied to the profile is driven by the effects of geometrical non-conformances on the efficiency and flow capacity of the aerofoil. However, this tolerance also has an impact on the ease with which the aerofoil can be manufactured, with tighter tolerance leading to lower manufacturing conformity. This paper details the application of an adjoint RANS solver and the according series of Design of Experiments (DoE) CFD calculations for a high pressure turbine blade to the above problem. There are two aims of this work; the first is to show that simpler linear CFD perturbation can be used to evaluate the effect of the geometric non-conformance. The second is to validate the spatial geometric correlation factor of the control points used in the manufacturing process on the performance evaluation with DoE techniques. This also verified the applicability of the adjoint CFD techniques; in fact the adjoint CFD calculation is an order of magnitude less computationally expensive than a large series of DoE RANS CFD calculations. The results confirm that the peak suction area is the most critical control region for the effect on the efficiency and flow capacity. Moreover, the CFD investigations show that a significant level of correlation exists between the influence factors at different control points. This suggests that not only the amount of geometric deviation but also the stream surface variation of profile tolerance significantly influence the final aerodynamic performance. The results from this calculation allow the creation of a 3D sensitivity map which will be used during the manufacturing of the aerofoil to optimise the control of the spatial distribution of the geometric non-conformance and to directly assess the expected performance effect during the manufacturing quality inspection. The methodology detailed in this paper shows how the CFD adjoint methods could be used for improved manufacturability of turbine blades ensuring that the critical characteristic features are controlled on the surface, relaxing the profile tolerance on those surface areas where the impact on the aerodynamic performance is predicted to be lower.
Gas turbine performance is highly dependent on the quality of the manufactured parts. Manufacturing variations in the parts can significantly alter the performance, especially efficiency and thus SFC. The legacy process is to accept variations within predefined profile tolerance limits and a few other qualitative parameters, mostly at a few, key two-dimensional aerofoil sections. With the widespread use of White light scans and other similar three-dimensional scans, this has improved to include the three-dimensional profile. The future however may lie with performance based quality assessment of manufactured parts, combined with quantitative surface quality assessment to implement an intelligent screening process for the parts. The adjoint method, typically used for shape optimization is adapted to provide a prediction of the impact on performance due to manufacturing variations. The work presented outlines a three stage quality assessment process for manufactured parts, involving three-dimensional profile tolerance based screening, followed by a surface curvature based screening and finally an Adjoint based performance prediction.
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