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Jet pump multi-objective optimization method based on neural network model and NSGA-II genetic algorithm

A neural network model and multi-objective optimization technology, applied in multi-objective optimization, constraint-based CAD, design optimization/simulation, etc., can solve problems that cannot meet engineering requirements, achieve high cost, improve hydraulic performance, and reduce calculations effect of difficulty

Pending Publication Date: 2021-06-11
HARBIN ENG UNIV
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Problems solved by technology

[0004] In addition, the existing optimization methods also focus on single-objective optimization, which cannot meet the actual engineering needs.

Method used

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  • Jet pump multi-objective optimization method based on neural network model and NSGA-II genetic algorithm
  • Jet pump multi-objective optimization method based on neural network model and NSGA-II genetic algorithm
  • Jet pump multi-objective optimization method based on neural network model and NSGA-II genetic algorithm

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Embodiment Construction

[0037] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0038] A jet pump multi-objective optimization method based on neural network model and NSGA-II genetic algorithm, the process is as follows figure 1 shown, including the following steps:

[0039] Step 1: Get the jet pump design parameters, optimization objectives, and constraints.

[0040] Jet pump structure such as figure 2 shown. The design parameters include the constriction angle α of the suction chamber, the diffusion angle β of the diffuser tube, the area ratio m, and the flow ratio q. Calculation formula of dimensionless parameters m and q:

[0041]

[0042]

[0043] In the formula, A is the outlet area of ​​the fluid nozzle, Q is the volume flow rate, and the subscripts w, s, and o are the working fluid at the inlet, the sucked fluid at the inlet, and the mixed fluid at the outlet, respectively.

[0044] The optim...

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Abstract

The invention provides a jet pump multi-objective optimization method based on a neural network model and an NSGA-II genetic algorithm. The method mainly comprises the steps that jet pump design parameters, optimization objectives and constraint conditions are determined, and sample point design parameters are obtained based on a sampling method; an optimization target value corresponding to the sample point design parameter through CFD software simulation is acquired. the sample point data is used to construct a neural network model of jet pump design parameters and an optimization target, and prediction precision is verified. based on the neural network model, an NSGA-II genetic algorithm is adopted to obtain a final optimization result. the CFD method is combined with the neural network model and the genetic algorithm, the problem that complex optimization design is difficult to solve due to multiple parameters and multiple disciplines is solved, the calculation difficulty is reduced, the problems that an optimization design method based on CFD simulation or experiments is high in cost and long in consumed time in the past are solved, multi-target optimization of the jet pump is achieved. The special design requirement for the lift ratio in actual engineering is met, and the hydraulic performance of the jet pump is effectively improved.

Description

technical field [0001] The invention relates to a jet pump optimization method, in particular to a jet pump multi-objective optimization method based on neural network model and NSGA-II genetic algorithm. Background technique [0002] Jet pumps are especially suitable for pumping fluids containing large amounts of solid particles (minerals, live fish, gravel, etc.). Therefore, it is widely used in engineering fields such as marine engineering, coastal engineering, and material transportation. Although the comprehensive utilization value of the jet pump is very high, the low energy transfer efficiency has always been the main factor affecting its further development. How to rationally design various structural parameters in jet pumps to optimize efficiency in different application environments is also a problem that plagues many experts. [0003] Although scholars at home and abroad have begun to study the optimization method of jet pumps, the overall research and analysis ...

Claims

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Application Information

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IPC IPC(8): G06F30/27G06F30/28G06F111/04G06F111/06G06F111/10G06F113/08G06F119/14
CPCG06F30/27G06F30/28G06F2111/06G06F2111/04G06F2111/10G06F2113/08G06F2119/14
Inventor 王立权徐凯孙文浩王刚运飞宏贾鹏王洪海鞠明李超
Owner HARBIN ENG UNIV
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