Optimization of Body Profile Line of Axial Flow Control Valve Based on Surrogate Model

doi:10.12141/j.issn.1000-565X.220306

Abstract

Abstract:

Aiming at the problems of long optimization cycle and mechanical repetition of the optimization process for large-diameter natural gas pipeline valves at home and abroad, this paper proposed a method for optimizing the profile of axial flow control valves using Kriging surrogate model combined with NSGA-Ⅱ algorithm. Taking the DN600 axial flow regulating valve as the research object, after preliminary evaluation of its performance by Fluent and ANSYS software, it selected the flow value, maximum stress level and maximum deformation as the optimization goals. First, the B-spline curve was used to analyze the valve body type. By changing the coordinates of the control points, the parameterization of the valve body profile could be realized, and the automatic modeling of the valve body profile could be realized. The Latin hypercube sampling method was used to design 100 types of profiles, and the structural optimization sample library was obtained through numerical simulation. Kriging surrogate model for an axial flow control valve was established. Then, the NSGA-Ⅱ algorithm was used to optimize the surrogate model to obtain the Pareto front solution set, and the optimal profile was determined by studying the front solutions of the three profiles and the velocity and pressure variation curves of the horizontal section inside the initial profile. The opening-resistance characteristics, flow-resistance characteristics and internal flow of the pipeline behind the valve were studied before and after optimization. The research results show that the optimized profile flow value increased by 9.2%, the maximum stress level decreased by 8.46%, and the maximum deformation is reduced by 6.2%, the fluid resistance is reduced after optimization, and the influence distance of high-speed flow in the pipeline after optimization is reduced. The performance improvement of the optimized profile proves the effectiveness of the profile optimization method and reveals the potential of the method in the field of valve profile structure optimization.

Key words: multi-objective optimization, profile line optimization, surrogate model, axial flow control valve, numerical simulation

CLC Number:

TH134

LI Shuxun, HU Yinggang, LI Cheng, et al. Optimization of Body Profile Line of Axial Flow Control Valve Based on Surrogate Model[J]. Journal of South China University of Technology(Natural Science Edition), 2023, 51(3): 41-52.

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节点数	网格数	最大应力值/MPa
181 246	149 776	117.82
318 026	203 775	118.24
338 405	250 694	118.43

设计变量	原始数值/mm	取值范围/mm
x₁	-333.4	-363.4～-303.4
y₁	307.2	277.2～337.2
x₂	-201.6	-221.6～-181.6
y₂	332.4	302.4～362.4
x₃	-105.8	-95.8～-115.8
y₃	390.1	360.1～420.1
x₄	402.0	372.0～432.0
y₄	456.9	426.9～486.9

x₂/mm	y₂/mm	x₃/mm	y₃/mm	x₄/mm	y₄/mm
-206.23	312.79	-96.61	366.78	406.34	439.22
-219.95	311.12	-104.67	385.73	376.88	476.76
-205.88	341.41	-106.02	394.27	421.51	449.23
-194.56	339.74	-115.63	372.46	395.05	478.97
-181.47	327.99	-98.56	365.47	412.66	429.67

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