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
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[0037] The present invention will be further described in further detail below with reference to the accompanying drawings.
[0038] Multi-objective optimization method based on neural network model and NSGA-II genetic algorithm, figure 1 As shown, including the following steps:
[0039] Step 1: Get the design parameters of the jet pump, optimize the goals, constraints.
[0040] Jet pump structure figure 2 Indicated. The design parameters contain the shrinkage angle α, the diffusion angle β, the area ratio M, and the flow ratio Q. Quasi-dimensional parameter M and Q calculation formula:
[0041]
[0042]
[0043] In the formula, a is the exit area of the fluid nozzle, Q is the volumetric flow, and the foot standard W, S, O is inlet at an inlet, respectively, and the inlet is mixed at the inlet and the outlet.
[0044] Optimization target contains the direction ratio H and efficiency η:
[0045]
[0046]
[0047] In the formula, P is static pressure, γ is a capacity, G is...
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