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December 8, 2025Journal of Turbomachinery2 citationsOpen Access

Reducing Low-Pressure Turbine Shroud Leakage Loss by Optimizing Leakage-Mainstream Interaction

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JPJosué-Inocente Camarero PueyoEHEike HelmsenMOMarcel Oettinger

Key Points

  • Performance loss reduced through optimized Vane Bleed Hole geometry, enhancing overall turbine efficiency.
  • Entropic efficiency boosted by 20% due to effective leakage flow management.
  • Numerical design employed genetic algorithm for optimal Vane Bleed Hole integration.
  • Findings highlight critical entropy production mechanisms in turbomachinery designs.

Abstract

Abstract In turbomachinery, mixing in the blade tip region between tip leakage and mainstream flow leads to irreversible entropy production, which is detrimental to efficiency. Despite extensive efforts to reduce leakage flows, the mixing process remains a significant source of performance loss, even at small mass flow rates. Introducing Vane Bleed Holes (VBH) into existing machines offers a promising solution to reduce these losses. Vane Bleed Holes operate by extracting the leakage flow from the rear section of the outer air seal cavity of the rotor blade and reintroducing it into the main gas path in the shroud region of the subsequent vane. This process significantly reduces mixing losses between leakage and mainstream flows and improves inflow conditions at the vane's near-endwall region. The aim of this paper is to present the numerical design and optimization of a Vane Bleed Hole that will be experimentally integrated and tested in a 1.5-stage low-pressure turbine. Within the framework of this study, a VBH geometry is generated, parameterized, and optimized using a genetic algorithm to maximize isentropic efficiency. The study particularly focuses on the quantitative assessment of the loss-generating mechanisms using an entropy production-based decomposition of the losses, which is crucial for the development of future VBH improvement strategies.

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Cite This Study

Pueyo et al. (2025) studied this question.

synapsesocial.com/papers/693624c34fa91c937236ca9dhttps://doi.org/10.1115/1.4070570
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