Dissertation > Industrial Technology > Machinery and Instrument Industry > Gas compression and transportation machinery > Compressors, compressor

Development of the Platform for Compressor Optimization Design and Aerodynamic Optimization Design in the Transonic Compressor

Author WuXiaoPeng
Tutor SongYanPing
School Harbin Institute of Technology
Course Power Machinery and Engineering
Keywords Axial Compressor Blad Genetic Algorithm Artificial Neural Network Optimization Platform Aerodynamic Optimization Design
Type Master's thesis
Year 2008
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Aerodynamic optimization design technology is an important research direction in turbomachinery design. Aerodynamic optimization technology for compressor design plays an important role in the development of high performance axial flow compressor. With the rapid development of computational fluid dynamics and optimization algorithm, the optimization techniques of turbomachinery have been developed speedly. But the aerodynamic optimization of the turbomachinery blade, especially the transonic compressor blade, is still a challenge area. In this paper, the optimization platform of the iSIGHT is used in one dimensional and quasi-three dimensional aerodynamic optimization design of axial flow compressor.At the same time, optimization design of the transonic compressor, is carried out for the minimization of the total energy loss coefficient, based on the software of Design3D-a presentation of the Numeca optimization enviroment of turbomachinery blades. These studies mainly consist of the following aspects:First, one dimension and quasi-three dimensional design method of multistage axial flow compressor was studied. Thanks to a combination of the Compressor program and the iSIGHT optimization enviroment, a compressor optimization platform has been established and is carried out for the minimization of the total energy loss coefficient in one dimension and quasi-three dimensional designs. Point to the character of compressor optimization design, axial flow compressor optimization method adopt as a fast elitist non-dominated sorting genetic algorithm (NSGA-11).Second, the detailed numerical simulation on the original blade profiles is done. The numerical results which ensure the computational reliability and establishe the base on following aerodynamic optimization work. the parameterized blade is obtained by stacking four blade sections along the span(hub, 10%span, 32%span,61%span, 85%span and tip), with the help of Autoblade,each blade section can be defined by the suction side and pressure side mode. Both suction and pressure sides are constructed in the form of a high degree Bezier Curve with respect to the camber line. And the camber line is parameterized by a three-order B-Spline. This will also provide variables for the following optimizationThird, the optimization design of a three dimensional blade profile was carried out for the reference transonic compressor. And it is based on the method that consists of three dimensiona Navier-Stokes flow computation, mesh generated automatically, three dimensional blade section parameterization and genetic algorithm integrated with artificial neural network. The optimization objective is minmum the total energy loss coefficient. Compared with the reference blade, the aerodynamic preformences of the optimized blade is improved obviously. The results show that this optimization method can control the intensity and the position of the inlet shockwave, weaken the flow separation, reduce the flow losses, and that the present method is the efficient way to get the compressor blade with the low flow losses and high eficiency.

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