Differential evolution based soft optimization to attenuate vane-rotor shock interaction in high-pressure turbines
This article presents a soft computing methodology to design turbomachinery components experiencing strong shock interactions. The study targets a reduction of unsteady phenomena using evolutionary optimization with robust, high fidelity, and low computational cost evaluations. A differential evolution (DE) algorithm is applied to optimize the transonic vane of a high-pressure turbine. The vane design candidates are examined by a cost-effective Reynolds-averaged Navier-Stokes (RANS) solver, computing the downstream pressure distortion and aerodynamic efficiency. A reduction up to 55% of the strength of the shock waves propagating downstream of the stand-alone vane was obtained. Subsequently to the vane optimization, unsteady computations of the vane-rotor interaction were performed using a non-linear harmonic (NLH) method. Attenuation above 60% of the unsteady forcing on the rotor (downstream of the optimal vane) was observed, with no stage-efficiency abatement. These results show the effectiveness of the proposed soft optimization to improve unsteady performance in modern turbomachinery exposed to strong shock interactions. (C) 2013 Elsevier B.V. All rights reserved.
vane-rotor shock interaction turbomachinery design optimization evolutionary algorithm