scholarly journals Parameter Analysis and Optimization of Annular Jet Pump Based on Kriging Model

2020 ◽  
Vol 10 (21) ◽  
pp. 7860
Author(s):  
Kai Xu ◽  
Gang Wang ◽  
Liquan Wang ◽  
Feihong Yun ◽  
Wenhao Sun ◽  
...  
Keyword(s):  
Global Optimization ◽  
Kriging Model ◽  
Optimization Method ◽  
Area Ratio ◽  
Pump Efficiency ◽  
Jet Pump ◽  
Pump Design ◽  
Annular Jet ◽  
Design Variables ◽  
Annular Jet Pump

Jet pump efficiency heavily relies on the geometrical parameters of the pump design and parameter global optimization in the full variable space is still a big challenge. This paper proposed a global optimization method for annular jet pump design combining computational fluid dynamics (CFD) simulation, the Kriging approximate model and experimental data. The suction angle, the flow ratio, the diffusion angle, and the area ratio are selected as the design variables for optimization. The optimal space filling design (OSF) method is used to generate sampling points from the design space of the four design variables. The optimization method solves the constrained optimization problem with a given head ratio by building the functional relationship established by the Kriging model between efficiency and design parameters, which makes the method more applicable. The design result shows that the annular jet pump efficiency is predicted well by the Kriging model; m is a key variable affecting the annular jet pump efficiency. As the area ratio m decreases, the mixing effect at the suction chamber outlet can be improved, but the frictional resistance increases.

scholarly journals Multi-Objective Optimization of Jet Pump Based on RBF Neural Network Model

2021 ◽  
Vol 9 (2) ◽  
pp. 236
Author(s):  
Kai Xu ◽  
Gang Wang ◽  
Luyao Zhang ◽  
Liquan Wang ◽  
Feihong Yun ◽  
...  
Keyword(s):  
Neural Network ◽  
Rbf Neural Network ◽  
Optimization Method ◽  
Approximate Model ◽  
Flow Ratio ◽  
Multi Objective Optimization ◽  
Jet Pump ◽  
Nsga Ii ◽  
Annular Jet ◽  
Annular Jet Pump

In this study, an annular jet pump optimization method is proposed based on an RBF (Radial Basis Function) neural network model and NSGA-II (Non-Dominated Sorting Genetic Algorithm) optimization algorithm to improve the hydraulic performance of the annular jet pump applied in submarine trenching and dredging. Suction angle, diffusion angle, area ratio and flow ratio were selected as design variables. The computational fluid dynamics (CFD) model was used for numerical simulation to obtain the corresponding performance, and an accurate RBF neural network approximate model was established. Finally, the NSGA-II algorithm was selected to carry out multi-objective optimization and obtain the optimal design variable combination. The results show that the determination coefficient R2 of the two objective functions (jet pump efficiency and head ratio) of the approximate model of the RBF neural network were greater than 0.97. Compared with the original model, the optimized model’s suction angle increased, and the diffusion angle, flow ratio and area ratio decreased. In terms of performance, the head ratio increased by 30.46% after the optimization of the jet pump, and efficiency increased slightly. The proposed jet pump performance optimization method provides a reference for improving the performance of other pumps.

scholarly journals A Kriging-Assisted Multi-Objective Constrained Global Optimization Method for Expensive Black-Box Functions

Mathematics ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 149
Author(s):  
Yaohui Li ◽  
Jingfang Shen ◽  
Ziliang Cai ◽  
Yizhong Wu ◽  
Shuting Wang
Keyword(s):  
Global Optimization ◽  
Pareto Frontier ◽  
Kriging Model ◽  
Optimization Method ◽  
Function Evaluation ◽  
Sampling Point ◽  
Constrained Global Optimization ◽  
Multi Objective ◽  
Sample Data ◽  
Sampling Points

The kriging optimization method that can only obtain one sampling point per cycle has encountered a bottleneck in practical engineering applications. How to find a suitable optimization method to generate multiple sampling points at a time while improving the accuracy of convergence and reducing the number of expensive evaluations has been a wide concern. For this reason, a kriging-assisted multi-objective constrained global optimization (KMCGO) method has been proposed. The sample data obtained from the expensive function evaluation is first used to construct or update the kriging model in each cycle. Then, kriging-based estimated target, RMSE (root mean square error), and feasibility probability are used to form three objectives, which are optimized to generate the Pareto frontier set through multi-objective optimization. Finally, the sample data from the Pareto frontier set is further screened to obtain more promising and valuable sampling points. The test results of five benchmark functions, four design problems, and a fuel economy simulation optimization prove the effectiveness of the proposed algorithm.

Annular Jet Pump

1959 ◽  
Vol 30 (4) ◽  
pp. 296-297 ◽  
Author(s):  
Werner H. Haak ◽  
Frederick Vrátný
Keyword(s):  
Jet Pump ◽  
Annular Jet ◽  
Annular Jet Pump

Two-dimensional numerical simulations on the performance of an annular jet pump

2002 ◽  
Vol 5 (1) ◽  
pp. 21-28 ◽  
Author(s):  
O. B. Kwon ◽  
M. K. Kim ◽  
H. C. Kwon ◽  
D. S. Bae
Keyword(s):  
Numerical Simulations ◽  
Two Dimensional ◽  
Jet Pump ◽  
Annular Jet ◽  
Annular Jet Pump

Recirculation in an Annular-Type Jet Pump

1994 ◽  
Vol 116 (4) ◽  
pp. 735-740 ◽  
Author(s):  
Donald F. Elger ◽  
Sam. J. Taylor ◽  
Chyr P. Liou
Keyword(s):  
Recirculation Zone ◽  
Area Ratio ◽  
Secondary Flows ◽  
Jet Pump ◽  
Flow Area ◽  
Pump Design ◽  
A Value

For some annular-type jet pump applications, it is important to avoid formation of a recirculation zone in the mixing region. The goals of this research were to find (i) when recirculation occurs and (ii) the size and location of the resulting recirculation zone. Experiments were performed using air in a straight-walled, annular-type, ducted jet. Area ratio Aj/As varied from 0.39 to 0.89; here, A is flow area, and j and s identify the jet and secondary flows, respectively. Data showed that recirculation correlates with J, where J ≈ Pj/(Pj + Ps), and P is rate of momentum. For the area ratios studied, recirculation begins when J exceeds a value ranging from 0.89 to 0.94. This paper also presents data showing the recirculation zone boundaries and presents a discussion of jet pump design.

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