Reliability-based design optimization of axial compressor using uncertainty model for stall margin

Reliability-based 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.

[1]  최재호 서지 마진 증가를 고려한 원심 압축기 설계 최적화 , 2008 .

[2]  Lingen Chen,et al.  Optimum design of a subsonic axial-flow compressor stage , 2005 .

[3]  Sung-Jong Kim,et al.  Design of new sound metric and its application for quantification of an axle gear whine sound by utilizing artificial neural network , 2009 .

[4]  Dieter Bestle,et al.  Application of multi-objective optimization to axial compressor preliminary design , 2006 .

[5]  Jin Shik Lim,et al.  Design Point Optimization of an Axial-Flow Compressor Stage , 1989 .

[6]  Jae-Ha Chai A Study on Centrifugal Compressor Design Optimization for Increasing Surge Margin , 2008 .

[7]  Ernesto Benini,et al.  Three-Dimensional Multi-Objective Design Optimization of a Transonic Compressor Rotor , 2003 .

[8]  Advisory Group for Aeronautical Research and Development , 1957, Nature.

[9]  Kwang‐Yong Kim,et al.  Design optimization of low-speed axial flow fan blade with three-dimensional RANS analysis , 2008 .

[10]  Wolfgang A. Kaysser,et al.  Materials and design concepts for high performance compressor components , 2003 .

[11]  Meng-Sing Liou,et al.  Multiobjective optimization using coupled response surface model and evolutionary algorithm , 2004 .

[12]  Nam-Ho Kim,et al.  Reliability-Based Design Optimization of a Transonic Compressor , 2005 .

[13]  Jae-Woo Lee,et al.  Optimal design of high temperature vacuum furnace using response surface method , 2008 .

[14]  Dong-Ho Lee,et al.  Strongly Coupled Method for 2DOF Flutter Analysis , 2006 .

[15]  Dong-Ho Lee,et al.  Aerodynamic Shape Design of Rotor Airfoils Undergoing Unsteady Motion , 2004 .

[16]  L. Reid,et al.  Design and overall performance of four highly loaded, high speed inlet stages for an advanced high-pressure-ratio core compressor , 1978 .

[17]  Meng-Sing Liou,et al.  Aerostructural Optimization of a Transonic Compressor Rotor , 2006 .

[18]  S. Pierret,et al.  Multidisciplinary and multiple operating points shape optimization of three-dimensional compressor blades , 2006 .

[19]  Meng-Sing Liou,et al.  Multiobjective Optimization of Rocket Engine Pumps Using Evolutionary Algorithm , 2002 .

[20]  Mark R. Anderson,et al.  CFD-Based Throughflow Solver in a Turbomachinery Design System , 2007 .

[21]  Michael G. Neubauer,et al.  D-optimal weighing designs for four and five objects , 1998 .

[22]  전용희,et al.  Application of the Robust and Reliability-Based Design Optimization to the Aircraft Wing Design , 2006 .

[23]  Young-Seok Choi,et al.  Design of axial fan using inverse design method , 2008 .

[24]  Dong-Ho Lee,et al.  Multi-Objective and Multidisciplinary Design Optimization of Supersonic Fighter Wing , 2006 .

[25]  이승하,et al.  연비를 고려한 차량 및 적응형 순항 제어기의 다분야 통합 최적설계 , 2009 .

[26]  Dong-Ho Lee,et al.  Application of Collaborative Optimization Using Genetic Algorithm and Response Surface Method to an Aircraft Wing Design , 2006 .

[27]  Meng-Sing Liou,et al.  Multiobjective Optimization Using Coupled Response Surface Model and Evolutionary Algorithm. , 2005 .

[28]  Tong Seop Kim,et al.  Analysis of performance deterioration of a micro gas turbine and the use of neural network for predicting deteriorated component characteristics , 2008 .

[29]  Dong-Ho Lee,et al.  Robust Design Optimization of a Fighter Wing Using an Uncertainty Model Constructed by Neural Network , 2008 .

[30]  Kwang-Yong Kim,et al.  Multi-objective optimization of an axial compressor blade , 2008 .