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<p>The accuracy of hollow turbine blades is influenced by the precision of the wax patterns that incorporate ceramic cores. The positioning and stabilization of the ceramic core within the mold are critical yet challenging during the wax pattern forming process. Wax supports provide a promising solution for this issue, as they offer sufficient support without risking damage to the ceramic core, unlike traditional metal supports. However, as wax materials tend to deform under injection pressure, optimizing the layout of wax supports became crucial to balance the load and maintain positioning accuracy. Considering the characteristics, a wax support layout optimization model was established in this paper to reduce positioning errors while adhering to the constraints of load balance, uniform load distribution, and wall thickness. The load on the ceramic core during the wax injection process was analyzed through numerical simulation, and the optimization model was solved using an adaptive genetic algorithm (AGA). The optimized layout was determined by the wax pressing experiment. The results demonstrated that the optimized wax support layout improved wall thickness accuracy by 31.4%, thereby establishing a foundation for enhancing casting precision.</p>

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Layout optimization method for wax supports on wax pattern ceramic core of hollow turbine blade

  • 期刊论文

  • 发表日期：

    2026年1月28日

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  • Yulong Wu,
  • Wenhu Wang,
  • Ruizhe Dong,
  • Zichun Wang,
  • Tianren Zhang,
  • Ruisong Jiang,
  • Kang Cui,
  • Yuanbin Wang

摘要

The accuracy of hollow turbine blades is influenced by the precision of the wax patterns that incorporate ceramic cores. The positioning and stabilization of the ceramic core within the mold are critical yet challenging during the wax pattern forming process. Wax supports provide a promising solution for this issue, as they offer sufficient support without risking damage to the ceramic core, unlike traditional metal supports. However, as wax materials tend to deform under injection pressure, optimizing the layout of wax supports became crucial to balance the load and maintain positioning accuracy. Considering the characteristics, a wax support layout optimization model was established in this paper to reduce positioning errors while adhering to the constraints of load balance, uniform load distribution, and wall thickness. The load on the ceramic core during the wax injection process was analyzed through numerical simulation, and the optimization model was solved using an adaptive genetic algorithm (AGA). The optimized layout was determined by the wax pressing experiment. The results demonstrated that the optimized wax support layout improved wall thickness accuracy by 31.4%, thereby establishing a foundation for enhancing casting precision.