Optimization Design And Associated Issues Of Gas Turbine Compressor Airfoil

Flow featured by high Reynolds number and high turbulence intensity inheavy-duty gas turbine deprives the advantages of traditional controlled diffusionairfoils, which take the advantage of delayed transition onset to improve theperformance. As the high Reynolds number and high turbulence intensity drive thetransition onset on suction side moves upstream towards the leading edge, it isnecessary to develop new CDA airfoils aiming at the very working conditions inheavy-duty gas turbines. From this point, this article carried out anauto-optimization design to develop a new cluster of airfoils with wide stall marginand low-loss operating range. The result turns out to be a satisfactory: newlyoptimized airfoils obtain wider operating ranges and their stall margins areincreased by30%comparing to the baseline. The design methodology of broadenthe stall margin is obtained through analysis and comparison of the baseline andoptimized airfoils.Airfoil optimization platform used in this article is based on commercialoptimization software Isight integrating a parameterized blade shape descriptionsoftware developed autonomously by HIT, two flow solvers (MISES and CFXsolver) and their post-processing modules. The function of generating airfoilparameters, flow field calculation and data processing can be achievedautomatically in this platform.The raw airfoil parameters are extracted from mid-span of three typical stators(1st,10thand16thstage) in a heavy-duty gas turbine compressor, which representcompressible and incompressible gas state.Parameterized blade shape description method based on NURB curve makesuse of the advantages of NURB curve. The parameters can embody the geometryfeatures of the blade shape and it’s convenient to modify. Blade shape can be easilycalculated from parameters. By using correct mathematical method, parameters canbe solved according to the blade shape points with sufficient precision. Severalparameterized blade shape description methods listed are limited in some aspectsand not quite suitable for optimistic designation. The optimization algorithm is Multi-Island Genetic Algorithm integrated inIsight software. Parameters in the algorithm are set respectively based on thecapacity of different flow field solvers in order to seek the best airfoils fromcandidates as comprehensive as possible. The type of objective function leads to adesign characterized by low loss at design point condition, a wide operating range, adefinite relative stall margin, a low and constant loss level within the inner80%incidence range, no violation of any geometric restrictions.MISES code developed by Drela and Gile from MIT and commercial simulationsoftware CFX are used in this optimization design. In MISES code, atwo-dimensional, steady-state and inviscid calculation of the flow field is coupledwith an integral, compressible boundary layer calculation. Both MISES and CFXsolvers can calculate the flow field considering transition with high accuracy,efficiency and reliability.The result turns out that the total pressure loss of optimized airfoils at designpoint increased as the stall margin and operating range get wider. The objectivefunction decreased, which satisfies the original anticipation.Then, the airfoils are stacked in straight line to get the optimized blade so thattheir performance in cascade can be examined. The results showed that theoptimized cascade improved the corner separation dramatically, which led to higherefficiency and performance.