Abstract
High efficiency and wide stability at variable speeds are equally important to the design and operation of multistage axial flow compressors. However, published research works on three-dimensional design optimization of compressors are so far mainly limited to a single blade row or stage at design speed due to the curse of dimensionality. Moreover, optimization of variable inlet guide vanes (IGV)/stators for off-design operations is carried out by using a rapid but low-fidelity prediction tool and is generally independent of design optimization of blade geometry. To tackle these issues, a three-dimensional holistic design and adjustment optimization method is developed in which both three-dimensional blade geometry and variable IGV/stators are optimized simultaneously for better efficiency and stability at design and off-design conditions. Metamodel-interpreted data mining method and adaptive infilling strategy are used respectively to enhance the capability of the metamodeling and optimization. The developed method is then applied to a modern highly loaded 3.5-stage transonic axial flow compressor at both design and part-design speeds. The results show that the stall margin is extended from 8.23% to 19.65% at 70% design speed while peak efficiency is slightly improved at design speed. The flow mechanisms responsible for the efficiency enhancement at design speed are mainly associated with the reduced total pressure loss in stators as well as inter- and intra-stage loading redistribution. The stability enhancement at 70% design speed is mainly achieved by loading the front blade rows while unloading the limiting rear blade row through variable IGV/stators adjustment. The developed holistic design and adjustment optimization method with the aid of metamodel-interpreted data mining is of great application value for the design and adjustment of advanced multistage axial flow compressors.
Issue Section:
Research Papers
Keywords:
multistage axial flow compressor,
variable inlet guide vanes and stators,
variable speeds,
design and adjustment optimization,
data mining,
compressor stall,
surge,
and operability,
fan,
compressor,
and turbine aerodynamic design,
turbomachinery blading design
Topics:
Blades,
Compressors,
Design,
Optimization,
Stability,
Stators,
Inlet guide vanes,
Axial flow,
Geometry,
Data mining,
Flow (Dynamics)
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