Modern gas turbines operate at ever-increasing inlet temperatures to maximize thermal efficiency and power output, subjecting turbine blades to severe thermal and mechanical stresses. To ensure component durability, effective cooling strategies are indispensable, yet they strongly influence the underlying aerothermal behavior, particularly in transonic regimes where shock–boundary layer interactions are critical. In this work, a comprehensive Reynolds-Averaged Navier–Stokes (RANS) investigation is carried out on the iconic LS89 transonic turbine cascade, considering both adiabatic and cooled wall conditions. Three operating cases, spanning progressively higher outlet Mach numbers, are analyzed using multiple turbulence closures. To mitigate the wellknown model dependence of RANS predictions, a model-averaging strategy is introduced, providing a more robust prediction framework and reducing the uncertainty associated with single-model results. A systematic mesh convergence study is also performed to ensure gridindependent solutions. The results show that while wall pressure and isentropic Mach number remain largely unaffected by wall cooling, viscous near-wall quantities and wake characteristics exhibit a pronounced sensitivity to the wall-to-recovery temperature ratio. To support further research and model benchmarking, the complete RANS database generated in this work is released as an open-source resource and made publicly available at https://github.com/ LS89-RANS-Data/LS89-RANS-data.
Modern gas turbines operate at ever-increasing inlet temperatures to maximize thermal efficiency and power output, subjecting turbine blades to severe thermal and mechanical stresses. To ensure component durability, effective cooling strategies are indispensable, yet they strongly influence the underlying aerothermal behavior, particularly in transonic regimes where shock–boundary layer interactions are critical. In this work, a comprehensive Reynolds-Averaged Navier–Stokes (RANS) investigation is carried out on the iconic LS89 transonic turbine cascade, considering both adiabatic and cooled wall conditions. Three operating cases, spanning progressively higher outlet Mach numbers, are analyzed using multiple turbulence closures. To mitigate the wellknown model dependence of RANS predictions, a model-averaging strategy is introduced, providing a more robust prediction framework and reducing the uncertainty associated with single-model results. A systematic mesh convergence study is also performed to ensure gridindependent solutions. The results show that while wall pressure and isentropic Mach number remain largely unaffected by wall cooling, viscous near-wall quantities and wake characteristics exhibit a pronounced sensitivity to the wall-to-recovery temperature ratio. To support further research and model benchmarking, the complete RANS database generated in this work is released as an open-source resource and made publicly available at https://github.com/ LS89-RANS-Data/LS89-RANS-data.
Aerothermodynamic impact of wall cooling in transonic gas turbine stators: RANS-based insights
FORNASARI, DAVIDE
2024/2025
Abstract
Modern gas turbines operate at ever-increasing inlet temperatures to maximize thermal efficiency and power output, subjecting turbine blades to severe thermal and mechanical stresses. To ensure component durability, effective cooling strategies are indispensable, yet they strongly influence the underlying aerothermal behavior, particularly in transonic regimes where shock–boundary layer interactions are critical. In this work, a comprehensive Reynolds-Averaged Navier–Stokes (RANS) investigation is carried out on the iconic LS89 transonic turbine cascade, considering both adiabatic and cooled wall conditions. Three operating cases, spanning progressively higher outlet Mach numbers, are analyzed using multiple turbulence closures. To mitigate the wellknown model dependence of RANS predictions, a model-averaging strategy is introduced, providing a more robust prediction framework and reducing the uncertainty associated with single-model results. A systematic mesh convergence study is also performed to ensure gridindependent solutions. The results show that while wall pressure and isentropic Mach number remain largely unaffected by wall cooling, viscous near-wall quantities and wake characteristics exhibit a pronounced sensitivity to the wall-to-recovery temperature ratio. To support further research and model benchmarking, the complete RANS database generated in this work is released as an open-source resource and made publicly available at https://github.com/ LS89-RANS-Data/LS89-RANS-data.| File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/99953