This paper presents a 3-D optimization of a moderately loaded transonic compressor rotor by means of a multiobjective optimization system. The latter makes use of a differential evolutionary algorithm in combination with an Artificial Neural Network and a 3D Navier-Stokes solver. Operating it on a cluster of 30 processors enabled the evaluation of the off-design performance and the exploration of a large design space composed of the camber line and spanwise distribution of sweep and chord length. Objectives were an increase of efficiency at unchanged stall margin by controlling the shock waves and off-design performance curve. First designs of single blade rows allowed a better understanding of the impact of the different design parameters. Forward sweep with unchanged camber improved the peak efficiency by only 0.3% with the same stall margin. Backward sweep with an optimized S shaped camber line improved the efficiency by 0.6% at unchanged stall margin. It is explained how the camber line control can introduce the same effect as forward sweep and compensate the expected negative effects of backward sweep. The best results (0.7% increase in efficiency and unchanged stall margin) have been obtained by a stage optimization that allows also a spanwise redistribution of the rotor flow and an increase of loading by extra flow turning. The latter compensates the loading shift induced by the backward sweep in order to reduce the inlet Mach number at the downstream stator hub.
This paper presents a 3-D optimization of a moderately loaded transonic compressor rotor by means of a multi-objective optimization system. The latter makes use of a Differential Evolutionary Algorithm in combination with an Artificial Neural Network and a 3D Navier-Stokes solver. Operating it on a cluster of 30 processors enabled the optimization of a large design space composed of the tip camber line and spanwise distribution of sweep and chord length. Objectives were an increase of efficiency at unchanged stall margin by controlling the shock waves and off-design performance curve. First, tests on a single blade row allowed a better understanding of the impact of the different design parameters. Forward sweep with unchanged camber improved the peak efficiency by only 0.3% with a small increase of the stall margin. Backward sweep with an optimized S shaped camber line improved the efficiency by 0.6% with unchanged stall margin. It is explained how the camber line control could introduce the forward sweep effect and compensate the negative effects of the backward sweep. The best results (0.7% increase in efficiency and unchanged stall margin) have been obtained by a stage optimization that also considered the spanwise redistribution of the rotor flow and loading to reduce the Mach number at the stator hub.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.