Multidisciplinary design optimization to reduce erosion of blades in a mixed flow fan

Abstract

This paper presents an anti-erosion design approach of multidisciplinary design optimization (MDO) for turbomachinery to improve the erosion resistance of the blades, and its application to the design of an industrial mixed flow fan is given. The method is based on a concept for turbomachinery anti-erosion design in the aerodynamic design stage by modifying the geometry of the turbomachinery. The MDO approach replaces the traditional time consuming design method through automatic analyses of the aerodynamic performance, stress distribution and erosion characteristics, controlled by the optimization strategy. In the MDO approach, a multi-objective optimization algorithm non-dominated sorting genetic algorithm-II combined with radial basis function meta-model is used to find the compromise between the conflicting demands of high-efficiency and low average erosion rate with constraints on the pressure ratio and the safety factor for the blade; finite element method is used to analyze the static mechanical responses of the blade; a Navier-Stokes solver is used to predict the aerodynamic performance; solid particle paths in a viscous flow are calculated by Lagrangian method, and then the prediction of erosion is performed based on Tabakoff erosion model. Both the aerodynamic and anti-erosion performances of three selected robust optimal solutions on the Pareto front are compared to those of the baseline. The results show that the main reason for the efficiency improvement of the optimized blades is probably the smaller flow separation region and weaker secondary flows. Further comparative analysis between the baseline blade and the compromise blade for the impinging parameters is presented, and the erosion rate of compromise blade can be considerably decreased due to the lower impact velocity, suitable impact angle and fewer impact times in comparison with that of the baseline blade. As a conclusion, it can be drawn that the proposed approach gives a further opportunity for turbomachinery anti-erosion design in consideration of other disciplines, and the methodology presented can be also applied to other turbomachinery and anti-erosion problem by a minor modification.

Intelligence design method for three-dimensional vaned diffusers in a centrifugal compressor

“…This solving strategy has good global performance and also can greatly save the calculating resources according to application experience of previously established LHS-RBF-NSGA-II optimization strategy. 31 Through above analysis, these results confirm that the high-performance 3DVD can be achieved through optimization combination of relevant decision variables. This process is controlled automatically by the NSGA-II algorithm, independently of experience of designers.…”

“…This solving strategy has good global performance and also can greatly save the calculating resources according to application experience of previously established LHS-RBF-NSGA-II optimization strategy. 31…”

“…The NSGA-II algorithm developed in-house has been demonstrated to have an excellent ability to deal with the MOP in our previous study. 31…”

“…The problem of the 3DVD design can be described by a Multi-objective Optimization Problem (MOP) to search the maximal stage isentropic efficiency and static pressure ratio within the universal design space. To solve the 3DVD design problem proposed here, an NSGA-algorithm, 30 which is a multi-objective evolution algorithm developed in our previous research, 31 is employed as an optimizer to seek Pareto solutions of the 3DVD design MOP. Finally, an automated and intelligent design platform of 3DVDs for a given centrifugal impeller is built.…”

A new methodology for multi-objective multidisciplinary design optimization problems based on game theory

“…Maheri and Isikveren (2013) developed a goal programming approach using a weight-free aggregate function to produce enhanced design alternatives for the multi-objective MDO problems. Wang, Wen, Li, and Xi (2014) combined the NSGA-II method with radial basis function meta-model to find the compromise between the conflicting demands in MDO of the blades in a mixed flow fan. Wang, Zhu, Wilamowska-Korsak, Bi, and Li (2014) proposed a systematic methodology to determine the variable weights of multiple objectives based on a modular neural network.…”