针对国内外大口径天然气管线阀门型线优化周期长、优化过程机械式重复的问题，提出一种采用Kriging代理模型结合NSGA-Ⅱ算法的轴流式调节阀型线优化方法。以DN600轴流式调节阀为研究对象，通过Fluent与ANSYS软件对其性能进行初步评估后，选定流量值、最大应力水平和最大变形量为优化目标。首先采用B-spline曲线对阀体型线进行拟合，通过改变控制点的坐标实现阀体型线的参数化，并实现阀体型线的自动建模，运用拉丁超立方采样方法设计100种型线，通过数值模拟得到结构优化样本库，建立轴流式调节阀的Kriging代理模型。然后采用NSGA-Ⅱ算法对代理模型进行寻优得到Pareto前沿解集，通过对3个型线前沿解与初始型线内部水平截面的速度、压力变化曲线的研究，确定最优型线。再对优化前后的开度-阻力特性、流量-阻力特性及阀后管道内部流动进行研究，结果表明，优化后的型线流量值提高了9.2%，最大应力水平降低了8.46%，最大变形量减小了6.2%，优化后流体阻力降低，阀后管道高速流动影响距离减小。优化后型线的性能提升证明了该型线优化方法的有效性，揭示了该方法在阀门型线结构优化领域的潜力。

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.