Abstract
A new design optimization method is proposed for the problem of high-precision aerodynamic design of multistage axial compressors. The method mainly contains three aspects: full-blade surface parametrization can significantly reduce the number of control variables per blade row and increase the degrees of freedom of the leading edge blade angle compared with the traditional semiblade parametric method; secondly, the artificial bee colony algorithm improved initialization and food source exploration and exploitation mechanism to enhance the global optimization ability and convergence speed, and a distributed optimization system is built on the supercomputing platform based on this method; finally, a phased optimization strategy based on the “synchronous change in multirow blades” is proposed, and expert experience is introduced to achieve a better balance between exploration and exploitation. The optimization method is applied to the AL-31F four-stage low-pressure compressor. As a result, the adiabatic efficiency is improved by 0.67% and the surge margin is improved by 3.1% under the premise that the total pressure ratio and mass flow rate satisfy the constraints, which verifies the effectiveness and engineering practicality of the proposed optimization method in the field of multistage axial flow compressor aerodynamic optimization.
Highlights
Aeroengines and gas turbines are needed for strategic national development, and one of the core components of aeroengines and gas turbines is the multistage axial flow compressor
Exp Sim (b) Mass flow-efficiency evolutionary algorithm, this paper proposes a phased optimization strategy based on the “synchronous change in multirow blades”; that is, the aerodynamic optimization process of the multistage axial compressor is divided into two phases, as Figure 6 shows
The phased optimization strategy based on the “synchronous change in multirow blades” can play a practical role in the aerodynamic optimization of multistage axial compressors for the following two reasons: (1) The optimized solution only exists in a few small local areas in the huge design space
Summary
Aeroengines and gas turbines are needed for strategic national development, and one of the core components of aeroengines and gas turbines is the multistage axial flow compressor. It is well known that the aerodynamic optimization design of a multistage axial flow compressor has the characteristics of typical high-dimensionality, expensive cost, and black box (HEB) [1] problem. Before the year 2000, limited by the computing power at that time, aerodynamic optimization of the multistage axial flow compressor was mainly limited to one dimension and two dimensions [2,3,4,5]. With the great improvement in computing power, three-dimensional steady aerodynamic optimization of compressors has been developed rapidly, and a few three-dimensional unsteady optimization methods have even been proposed [6]. Research on multistage axial flow compressors still mainly focuses on three-dimensional steady optimization. With the development of optimization regarding multidiscipline and high-fidelity problems, the HEB
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