Faculty Publications

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Author: search.filters.author.Babu, S.Subject: search.filters.subject.End-wall

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    An aerothermal investigation of purge flow behaviour in a linear turbine cascade with upstream wakes
    (Bentham Science Publishers, 2018) Babu, S.; Anish, S.
    Background: Over all efficiency of a turbofan engine can be improved by increasing turbine inlet temperature. To withstand the high turbine inlet temperatures advanced cooling techniques and robust materials are required. Air supplied from compressor can be used to purge turbine components and disk cavities from the incoming hot gas. Objective: In the present study, an attempt is made to understand the aerodynamic and thermal effects caused by the purge flow in the presence of stationary upstream wakes. Methods: Reynolds Averaged Navier Stokes Equation coupled with SST turbulence model is used for computational study. Base case experimental data conducted on a 5 blade linear cascade is used for numerical validation. The coolant to mainstream blowing ratio is varied from 0.2 to 1.2 with a step size of 0.2. Results: It is observed that with an increase in the blowing ratio, the mass averaged total pressure losses also increase. Purge flow shifts the passage vortex away from the endwall and causes significant overturning up to a span of 30-40mm, before they exhibit underturning up to midspan. In an effort to reduce the losses, purge ejection angle is reduced to 45° from 90°. Significant loss reduction and improved endwall protection are observed at 45° ejection angle. This ejection angle provides enough acceleration and momentum to the fluid inside the endwall boundary layer. But the upstream secondary wakes and secondary flows enhanced the mixing losses within the blade passage. Conclusion: The turbulent mixing generated by upstream wakes reduced the film cooling effectiveness over the endwall. The numerical results show that film cooling effectiveness can be improved by reducing the purge ejection angle. Various patents have been discussed in this article. © 2018 Bentham Science Publishers.
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    Mitigation of secondary flows and pressure side bubble in turbine blade passage using asymmetric endwall contouring: a steady-state analysis
    (Institute of Physics, 2025) Babu, S.; Jannet, S.; Raja, R.; Lionel, P.; Oommen, L.P.; Surendran, A.
    In turbine passages, secondary vortices and pressure-side bubbles significantly contribute to aerodynamic losses and reduced blade efficiency issues that are critical in industrial gas turbine performance. Hence, it is very important to mitigate such losses to enhance overall turbine efficiency. Several research attempts have already been made to address this challenge; however, most studies have not focused explicitly on pressure-side bubble mitigation strategies. In the present investigation, an effort has been made to investigate the impact of endwall contouring in minimizing losses caused by secondary vortices, particularly focusing on pressure-side bubble formation. Experimental and numerical investigations are conducted on a low-speed blowing-type turbine cascade wind tunnel. The experimental study involves in-cascade testing, while numerical simulations are performed using ANSYS Reynolds-Averaged Navier–Stokes (RANS) equations with the Shear Stress Transport (SST) turbulence model. Three contouring configurations (EC 1, EC 2, and EC 3) are compared against a non-profiled base case (BC). The results confirm that endwall curvature significantly alters secondary flow behavior and static pressure distribution. While EC 1 and EC 2 generated stagnant zones in the valleys, causing additional losses while the EC 3 profile with optimized hump height and valley depth, redistributed pressure effectively. This effectively suppressed lateral flow migration and pressure-side bubble formation, which in turn enhanced overall turbine performance. In comparison to the base case, the EC 3 design quantitatively reduced total pressure loss by 3.43%, proving its efficacy in improving aerodynamic performance. © 2025 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.