The objective of this paper is to present a fast and reliable CFD model that is able to simulate stationary and transient operations of multistage compressors and turbines. This analysis tool is based on an adapted ve...The objective of this paper is to present a fast and reliable CFD model that is able to simulate stationary and transient 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 calculated characteristic maps are compared to experimental ones.展开更多
Existing aerodynamic design systems for multi-stage axial-flow compressor suffer from several limitations,such as experience dependent models and time costly simulations.Few attempts,however,have been devoted to the r...Existing aerodynamic design systems for multi-stage axial-flow compressor suffer from several limitations,such as experience dependent models and time costly simulations.Few attempts,however,have been devoted to the rapid and automatic optimization of aerodynamic performance at the preliminary design phase,which plays a crucial role in the final aerodynamic performance.In this work,a rapid and automatic aerodynamic optimal design method is developed for the multi-stage axial-flow compressor based on one-dimensional meanline design method,radial-equilibrium equation and genetic algorithm.The one-dimensional performance prediction model includes some popular empirical correlations to calculate the flow loss,incidence angle,deviation angle and flow blockage.The radial-equilibrium equation is solved to obtain the spanwise distribution of aerodynamic and thermodynamic parameters at the inlet and outlet of each blade row.The genetic algorithm is used for an automatic search of the global optimal compressor configuration aiming at maximizing the design efficiency.The developed method is illustrated with the aerodynamic optimal design of a 6-stage axial-flow industry compressor and verified by computational fluid dynamics simulations.The results show that the developed method is capable of improving effectively the design efficiency and predicting accurately the aerodynamic performance of the 6-stage axial-flow industry compressor in a few minutes.This work is of scientific significance to improve the axial-flow compressor design system and of engineering importance to release the designers from the heavy experience dependence especially at the preliminary design phase.展开更多
文摘The objective of this paper is to present a fast and reliable CFD model that is able to simulate stationary and transient 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 calculated characteristic maps are compared to experimental ones.
基金This work is financially supported by the National Key Research and Development Project of China(Grant No.2016YFB0200901)National Natural Science Foundation of China(Grant No.51776154)+1 种基金National Science and Technology Major Project of China(Grant No.2017-II-0006-0020)Shaanxi Key Research and Development Project(Grant No.2018KWZ-01).
文摘Existing aerodynamic design systems for multi-stage axial-flow compressor suffer from several limitations,such as experience dependent models and time costly simulations.Few attempts,however,have been devoted to the rapid and automatic optimization of aerodynamic performance at the preliminary design phase,which plays a crucial role in the final aerodynamic performance.In this work,a rapid and automatic aerodynamic optimal design method is developed for the multi-stage axial-flow compressor based on one-dimensional meanline design method,radial-equilibrium equation and genetic algorithm.The one-dimensional performance prediction model includes some popular empirical correlations to calculate the flow loss,incidence angle,deviation angle and flow blockage.The radial-equilibrium equation is solved to obtain the spanwise distribution of aerodynamic and thermodynamic parameters at the inlet and outlet of each blade row.The genetic algorithm is used for an automatic search of the global optimal compressor configuration aiming at maximizing the design efficiency.The developed method is illustrated with the aerodynamic optimal design of a 6-stage axial-flow industry compressor and verified by computational fluid dynamics simulations.The results show that the developed method is capable of improving effectively the design efficiency and predicting accurately the aerodynamic performance of the 6-stage axial-flow industry compressor in a few minutes.This work is of scientific significance to improve the axial-flow compressor design system and of engineering importance to release the designers from the heavy experience dependence especially at the preliminary design phase.
