신경망 최적화 기법을 이용한 다익 홴/스크롤 시스템의 설부에 대한 형상 최적화

Abstract

In order to improve efficiency of a system with three-dimensional flow characteristics, this paper presents a new method that overcomes three-dimensional effects by using two-dimensional CFO and neural network. The method was applied to shape optimization of cut-off in a multi-blade fan/scroll system. As the entrance conditions of two-dimensional CFO, the experimental values at the positions out of the inactive zone were used. The distributions of velocity and pressure obtained by two-dimensional CFO were compared with those of three-dimensional CFO and experimental results. Itbr/ was found that the distributions of velocity and pressure have qualitative similarity. The results ofbr/ two-dimensional CFO were used for learning as target values of neural network. The optimal angle and radius of cut-off were determined as 71˚ and 0.092 times the outer diameter of impeller, respectively. It is quantified in the previous report that the optimal angle and radius of cut-off are approximately 72˚ and 0.08 times the outer diameter of impeller, respectively.br/