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<p>As a critical component in gas turbines, the guide vane must exhibit well-controlled microstructural characteristics—such as grain refinement and crystallographic orientation—to ensure high performance. However, conventional studies often focus on microstructure optimization alone, limiting improvements in overall casting quality. This study proposes an integrated numerical and experimental framework to investigate grain evolution during the investment casting of turbine guide vanes. A coupled cellular automaton and finite element approach is applied to simulate grain morphology under varying pouring speeds and nucleation parameters. The simulation results are validated through scanning electron microscopy and compositional analysis. It is found that moderately increasing the pouring speed enhances melt flow and nucleation kinetics, leading to finer grains and a higher proportion of equiaxed structures. Further, increasing the average bulk nucleation undercooling promotes grain refinement and equiaxed grain formation. The simulated grain evolution agrees well with experimental observations, demonstrating the applicability of this modeling strategy to complex thin-walled castings. Moreover, titanium-rich second-phase particles observed along grain boundaries support the predicted microstructural features. This study offers a practical basis for microstructure control in the investment casting of high-temperature alloy components.</p>

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Coupled Investigation of Process Parameters and Grain Structure Evolution in Investment Cast Turbine Blades

  • 期刊论文

  • 发表日期：

    2025年9月20日

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  • Chen Xiong,
  • Shu Wang,
  • Ruirun Chen,
  • Weipeng Xu,
  • Jiacheng Pan,
  • Dezhi Chen,
  • Hongze Fang,
  • Qiuju Zhu,
  • Xiaoming Wang,
  • Yanbo Liu,
  • Yalong Gao,
  • Jingjie Guo

摘要

As a critical component in gas turbines, the guide vane must exhibit well-controlled microstructural characteristics—such as grain refinement and crystallographic orientation—to ensure high performance. However, conventional studies often focus on microstructure optimization alone, limiting improvements in overall casting quality. This study proposes an integrated numerical and experimental framework to investigate grain evolution during the investment casting of turbine guide vanes. A coupled cellular automaton and finite element approach is applied to simulate grain morphology under varying pouring speeds and nucleation parameters. The simulation results are validated through scanning electron microscopy and compositional analysis. It is found that moderately increasing the pouring speed enhances melt flow and nucleation kinetics, leading to finer grains and a higher proportion of equiaxed structures. Further, increasing the average bulk nucleation undercooling promotes grain refinement and equiaxed grain formation. The simulated grain evolution agrees well with experimental observations, demonstrating the applicability of this modeling strategy to complex thin-walled castings. Moreover, titanium-rich second-phase particles observed along grain boundaries support the predicted microstructural features. This study offers a practical basis for microstructure control in the investment casting of high-temperature alloy components.