Impellers of helicon-axial multiphase pump are optimized based on CFD and genetic algorithm. The method mainly includes: CFD numerical calculation, to establish nonlinear relation through neural network, and genetic algorithm optimization extreme. Firstly, the profile of blades is parametric by spline surface and Choose 12 control points as optimization variables. Then, every optimization variable is given optimal dimension. Finally, sample database is got by using standard L27_3_13 orthogonal design table. Next, output values are got by modeling every sample, meshing generation and using CFD numerical calculation. Train neural networks through the database; thus the nonlinear relation between the blade parameter and pump performance parameters is built by applying the nonlinear fitting ability of BP neural networks. Regard the trained neural network as a fitness function of the genetic algorithm and use the characteristic of nonlinear global optimization of genetic algorithm to optimize the multiphase pump. Optimization result shows that the hydraulic efficiency of the multiphase pump is increased by 1.91%.
목차
Abstract 1. Introduction 2. Optimization Design Process 3. Impellers Parameterization 4. CFD Numerical Calculation 4.1. Model Establishment 4.2. Governing Equation 4.3. Governing Equation 4.4. Two-Phase Flow Model, Equations and Boundary Condition 5. Nonlinear Fitting of BP Neural Network 6. Comparative Analysis of Optimal Solutions 7. Conclusions References
키워드
multiphase pumpCFDneural networkgenetic algorithm
저자
Hu Hao [ School of Electric Power, North China University of Water Resources and Electric Power, Henan 450011, China, North China Electric Power University, Key Laboratory of CMCPPE Ministry of Education, Beijing 102206, China ]
Li Xinkai [ North China Electric Power University, Key Laboratory of CMCPPE Ministry of Education, Beijing 102206, China ]
Gu Bo [ School of Electric Power, North China University of Water Resources and Electric Power, Henan 450011, China ]
보안공학연구지원센터(IJGDC) [Science & Engineering Research Support Center, Republic of Korea(IJGDC)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Grid and Distributed Computing
간기
격월간
pISSN
2005-4262
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Grid and Distributed Computing Vol.8 No.6