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Design Optimization of a VX Gasket Structure for a Subsea Connector Based on the Kriging Surrogate Model-NSGA-II Algorithm Considering the Load Randomness

机译:考虑载荷随机性的基于克里格代理模型-NSGA-II算法的海底连接器VX垫片结构设计优化

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The VX gasket is an important part of the wellhead connector for a subsea Christmas tree. Optimization of the gasket’s structure can improve the connector’s sealing performance. In this paper, we develop an optimization approach for the VX gasket structure, taking into consideration working load randomness, based on the Kriging surrogate model-NSGA-II algorithm. To guarantee the simulation accuracy, a random finite element (R-FE) model of the connector’s sealing structure was constructed to calculate the gasket’s sealing performance under random working load conditions. The working load’s randomness was simulated using the Gaussian distribution function. To improve the calculation efficiency of the sealing performance for individuals within the initial populations, Kriging surrogate models were constructed. These models accelerated the optimization speed, where the training sample was obtained using an experimental method design and the constructed R-FE model. The effectiveness of the presented approach was verified in the context of a subsea Christmas tree wellhead connector, which matched the 20'' casing head. The results indicated that the proposed method is effective for VX gasket structure optimization in subsea connectors, and that efficiency was significantly enhanced compared to the traditional FE method.
机译:VX垫圈是用于水下圣诞树的井口连接器的重要组成部分。垫圈结构的优化可以提高连接器的密封性能。在本文中,我们基于Kriging替代模型-NSGA-II算法,考虑了工作载荷的随机性,为VX垫片结构开发了一种优化方法。为了保证模拟的准确性,构建了连接器密封结构的随机有限元(R-FE)模型,以计算垫圈在随机工作负载条件下的密封性能。使用高斯分布函数模拟了工作负荷的随机性。为了提高初始种群中个体密封性能的计算效率,构建了克里格代理模型。这些模型加快了优化速度,其中使用实验方法设计和构建的R-FE模型获得了训练样本。在与20英寸套管头匹配的海底圣诞树井口连接器的背景下,验证了所提出方法的有效性。结果表明,该方法对于海底连接器的VX垫片结构优化是有效的,与传统的有限元方法相比,效率得到了显着提高。

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