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    High-Fidelity Simulations of a High-Pressure Turbine Vane Subject to Large Disturbances: Effect of Exit Mach Number on Losses 

    Source: Journal of Turbomachinery:;2021:;volume( 143 ):;issue: 009:;page 091002-1
    Author(s): Zhao, Yaomin; Sandberg, Richard D.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: We report on a series of highly resolved large-eddy simulations of the LS89 high-pressure turbine (HPT) vane, varying the exit Mach number between Ma = 0.7 and 1.1. In order to accurately resolve the blade boundary layers ...
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    Using a New Entropy Loss Analysis to Assess the Accuracy of RANS Predictions of an High-Pressure Turbine Vane 

    Source: Journal of Turbomachinery:;2020:;volume( 142 ):;issue: 008:;page 081008-1
    Author(s): Zhao, Yaomin; Sandberg, Richard D.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Entropy loss is widely used to quantify the efficiency of components in turbomachines, and empirical relations have been developed to estimate the contribution of different mechanisms. However, further analysis is still ...
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    High-Fidelity Simulation Study of the Unsteady Flow Effects on High-Pressure Turbine Blade Performance 

    Source: Journal of Turbomachinery:;2022:;volume( 145 ):;issue: 001:;page 11002-1
    Author(s): Leggett, John; Zhao, Yaomin; Sandberg, Richard D.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Unsteadiness, in the form of both broadband background disturbances and discrete coherent wakes, can have a strong effect on the performance of turbomachinery blades. The influence of the incoming flow has received much ...
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    Integration of Machine Learning and Computational Fluid Dynamics to Develop Turbulence Models for Improved Low-Pressure Turbine Wake Mixing Prediction 

    Source: Journal of Turbomachinery:;2021:;volume( 143 ):;issue: 012:;page 0121001-1
    Author(s): Akolekar, Harshal D.; Zhao, Yaomin; Sandberg, Richard D.; Pacciani, Roberto
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: This paper presents the development of accurate turbulence closures for low-pressure turbine (LPT) wake mixing prediction by integrating a machine-learning approach based on gene expression programming (GEP), with ...
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    Large Eddy Simulation and RANS Analysis of the End-Wall Flow in a Linear Low-Pressure-Turbine Cascade—Part II: Loss Generation 

    Source: Journal of Turbomachinery:;2019:;volume( 141 ):;issue: 005:;page 51004
    Author(s): Marconcini, Michele; Pacciani, Roberto; Arnone, Andrea; Michelassi, Vittorio; Pichler, Richard; Zhao, Yaomin; Sandberg, Richard
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In low-pressure turbines (LPT) at design point, around 60–70% of losses are generated in the blade boundary layers far from end walls, while the remaining 30–40% is controlled by the interaction of the blade profile with ...
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    A Data-Driven Approach for Generalizing the Laminar Kinetic Energy Model for Separation and Bypass Transition in Low- and High-Pressure Turbines 

    Source: Journal of Turbomachinery:;2024:;volume( 146 ):;issue: 009:;page 91005-1
    Author(s): Fang, Yuan; Zhao, Yaomin; Akolekar, Harshal D.; Ooi, Andrew S. H.; Sandberg, Richard D.; Pacciani, Roberto; Marconcini, Michele
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: No common laminar kinetic energy (LKE) transition model has to date been able to predict both separation-induced and bypass transition, both phenomena commonly found in low-pressure turbines and high-pressure turbines. ...
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