Scholarlink

<p>Three-way control combiner valves (TCCVs) are critical components used in nuclear power plants to regulate the concentration of boron acid for neutron absorption and reactor safety. However, current TCCV designs often suffer from suboptimal control performance and high flow resistance, leading to control deviations and reduced operational efficiency. In this paper, a numerical model based on the standard <i>K</i>–<i>ω</i> turbulence model is established and validated against experimental data to analyze the flow characteristics and local flow resistance of a TCCV. A parametric design method for the throttling windows is proposed, establishing relationships between shape parameters and performance indexes, including control performance and flow resistance. The adaptive non-dominated sorting genetic algorithm (ANSGA-II) is used to optimize the shape parameters of the throttling windows. The optimization results show an improvement in the performance indexes of the TCCV, with the adjustable operating range increasing by 31.0% and the maximum local resistance decreasing by 18.3%. We also introduce the concepts of effective and controllable domains to characterize the inlet backflow phenomena and regulation dead zones, which are crucial for ensuring the reliability and effectiveness of control valves. These findings provide insights for enhancing the design and performance of TCCVs in nuclear power plants.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Optimization of throttling windows to improve flow control of three-way control combiner valves

  • 期刊论文

  • 发表日期：

    2026年2月6日

查看全文
  • Jin-yuan Qian,
  • Zhe-hui Ma,
  • Shi-jie Lin,
  • Chuang Liu,
  • Yu-wei Wang,
  • Fei Ling,
  • Liang Zhang,
  • Man-man Cui,
  • Tian-zuo Qu,
  • Zhi-jiang Jin

摘要

Three-way control combiner valves (TCCVs) are critical components used in nuclear power plants to regulate the concentration of boron acid for neutron absorption and reactor safety. However, current TCCV designs often suffer from suboptimal control performance and high flow resistance, leading to control deviations and reduced operational efficiency. In this paper, a numerical model based on the standard K–ω turbulence model is established and validated against experimental data to analyze the flow characteristics and local flow resistance of a TCCV. A parametric design method for the throttling windows is proposed, establishing relationships between shape parameters and performance indexes, including control performance and flow resistance. The adaptive non-dominated sorting genetic algorithm (ANSGA-II) is used to optimize the shape parameters of the throttling windows. The optimization results show an improvement in the performance indexes of the TCCV, with the adjustable operating range increasing by 31.0% and the maximum local resistance decreasing by 18.3%. We also introduce the concepts of effective and controllable domains to characterize the inlet backflow phenomena and regulation dead zones, which are crucial for ensuring the reliability and effectiveness of control valves. These findings provide insights for enhancing the design and performance of TCCVs in nuclear power plants.