A Quasi-One-Dimensional CFD Model for Multistage Turbomachines

来源 :Journal of Thermal Science | 被引量 : 0次 | 上传用户:no3ice
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The objective of this paper is to present a fast and reliable CFD model that is able to simulate stationary and tran- sient operations of multistage compressors and turbines.This analysis tool is based on an adapted version of the Euler equations solved by a time-marching,finite-volume method.The Euler equations have been extended by including source terms expressing the blade-flow interactions.These source terms are determined using the ve- locity triangles and a row-by-row representation of the blading at mid-span.The losses and deviations undergone by the fluid across each blade row are supplied by correlations.The resulting flow solver is a performance pre- diction tool based only on the machine geometry,offering the possibility of exploring the entire characteristic map of a multistage compressor or turbine.Its efficiency in terms of CPU time makes it possible to couple it to an optimization algorithm or to a gas turbine performance tool.Different test-cases are presented for which the cal- culated characteristic maps are compared to experimental ones. The objective of this paper is to present a fast and reliable CFD model that is able to simulate stationary and tran- sient operations of multistage compressors and turbines. This analysis tool is based on an adapted version of the Euler equations solved by a time-marching , finite-volume method. The Euler equations have been extended by including source terms expressing the blade-flow interactions. These source terms are determined using the ve-locity triangles and a row-by-row representation of the blading at mid-span. The losses and deviations undergone by the fluid across each blade row are supplied by correlations.The resulting flow solver is a performance pre- diction tool based only on the machine geometry, offering the possibility of exploring the entire characteristic map of a multistage compressor or turbine .Its efficiency in terms of CPU time makes it possible to couple it to an optimization algorithm or to a gas turbine performance tool. Different test-cases are presented for whic h the cal-culated characteristic maps are compared to experimental ones.
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