Centrifugal compressors are required to increase their operating range and efficiency, which are limited at low mass flow rates by the rotating stall and surge. This paper presents a surrogate-based multi-objective optimization of a centrifugal compressor to improve its efficiency and stall margin. Curvatures of the blade, the impeller shroud, and the diffuser hub are selected as optimization parameters since they influence highly both the efficiency and the stall limit. The implemented optimization procedure starts by the construction of a metamodel, which is the radial basis function that uses a database composed of a well-selected set of geometries and their corresponding computational fluid dynamics predicted objectives using the Ansys-CFX 12 code. The NSGA-II optimization algorithm is used afterward to search the Pareto front based on radial basis function approximations. To improve the accuracy of the radial basis function and subsequently the Pareto front, a database refinement is sequentially achieved, using the leave-one-out-cross-validation uncertainty to select infill points. The present procedure is tested on the NASA lowspeed centrifugal compressor, showing its ability to increase both the compressor operating range and efficiency. Furthermore, the flow pattern analysis confirms the suppression of separations that lead to instability in the optimized compressor at the stall point of the baseline design.

Surrogate-based shape optimization of stall margin and efficiency of a centrifugal compressor

BENINI, ERNESTO;BEDON, GABRIELE
2015

Abstract

Centrifugal compressors are required to increase their operating range and efficiency, which are limited at low mass flow rates by the rotating stall and surge. This paper presents a surrogate-based multi-objective optimization of a centrifugal compressor to improve its efficiency and stall margin. Curvatures of the blade, the impeller shroud, and the diffuser hub are selected as optimization parameters since they influence highly both the efficiency and the stall limit. The implemented optimization procedure starts by the construction of a metamodel, which is the radial basis function that uses a database composed of a well-selected set of geometries and their corresponding computational fluid dynamics predicted objectives using the Ansys-CFX 12 code. The NSGA-II optimization algorithm is used afterward to search the Pareto front based on radial basis function approximations. To improve the accuracy of the radial basis function and subsequently the Pareto front, a database refinement is sequentially achieved, using the leave-one-out-cross-validation uncertainty to select infill points. The present procedure is tested on the NASA lowspeed centrifugal compressor, showing its ability to increase both the compressor operating range and efficiency. Furthermore, the flow pattern analysis confirms the suppression of separations that lead to instability in the optimized compressor at the stall point of the baseline design.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3181486
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