Reliabilitybased design optimization of axial compressor using uncertainty model for stall margin Sangwon Hong, Saeil Lee, Sangook Jun, DongHo Lee*, Hyungmin Kang, YoungSeok Kang, SooSeok Yang
The Journal of Mechanical Science and Technology, vol. 25, no. 3, pp.731740, 2011
Abstract : Reliabilitybased design optimization (RBDO) of the NASA stage 37 axial compressor is performed using an uncertainty model for
stall margin in order to guarantee stable operation of the compressor. The main characteristics of RBDO for the axial compressor are
summarized as follows: First, the values of mass flow rate and pressure ratio in stall margin calculation are defined as statistical models
with normal distribution for consideration of the uncertainty in stall margin. Second, Monte Carlo Simulation is used in the RBDO process
to calculate failure probability of stall margin accurately. Third, an approximation model that is constructed by an artificial neural
network is adopted to reduce the time cost of RBDO. The present method is applied to the NASA stage 37 compressor to improve the
reliability of stall margin with both maximized efficiency and minimized weight. The RBDO result is compared with the deterministic
optimization (DO) result which does not include an uncertainty model. In the DO case, stall margin is slightly higher than the reference
value of the required constraint, but the probability of stall is 43%. This is unacceptable risk for an aircraft engine, which requires absolutely
stable operation in flight. However, stall margin obtained in RBDO is 2.7% higher than the reference value, and the probability of
success increases to 95% with the improved efficiency and weight. Therefore, RBDO of the axial compressor for aircraft engine can be a
reliable design optimization method through consideration of unexpected disturbance of the flow conditions.
Keyword :
Axial compressor; Reliabilitybased design optimization; Stall margin; Uncertainty model; Multidisciplinary design optimization
