Numerical Study of Purge and Secondary Flows in a Low Pressure Turbine

Cui, Jiahuan; Tucker, PG

doi:10.1115/gt2016-56789

Cited by 10 publications

(11 citation statements)

References 16 publications

(24 reference statements)

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“…Schuler et al (2011) noticed boundary layer thickening for different seal geometries and found that compound seal geometry reduced radial penetration of purge flow into mainstream and also restricts hot gas ingress into the wheel space. This hub passage vortex, radial penetration was also observed by Cui and Tucker (2017) and Chen et al (2018) in the presence of purge flow.…”

Section: Introductionsupporting

confidence: 63%

Computational Predictions of Velocity Ratio and Ejection Angle on Purge Flow in a Linear Turbine Cascade with Upstream Disturbance

Babu

Anish

2020

JAFM

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Secondary air bled from the compressor which bypasses the combustion chamber is used to seal the turbine components from incoming hot gas. Interaction of this secondary air or purge flow with the mainstream can alter the flow characteristics of turbine blade passage. An in depth analysis of secondary loss generation by purge flow in the presence of upstream disturbances has huge relevance. The objective of present study is to understand the aerodynamic and thermal effects caused by the purge coolant flow in the presence of an upstream wake. A linear turbine cascade is selected for the computational study and a stationary cylindrical rod which resembles the trailing edge of nozzle guide vane is kept 20 mm before the leading edge to generate the upstream wake (or disturbance). Purge flow disturbances includes strong formation of Kelvin-Helmholtz vortices at trailing edge and additional roll-up vortices at leading edge. Detailed analysis is carried out by varying the velocity ratios as well as the ejection flow angle. Higher velocity ratio and perpendicular coolant ejection reduces the mainstream axial momentum which enhances the passage cross flow. Even though the mass averaged total pressure loss is linearly dependent on the velocity ratio, a reduction in the ejection angle brings down the loss coefficient at the blade exit. A lower ejection angle will improve the film cooling effectiveness also. The presence of purge flow causes an increase in the overturning and underturning.

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Section: Introductionsupporting

confidence: 63%

Computational Predictions of Velocity Ratio and Ejection Angle on Purge Flow in a Linear Turbine Cascade with Upstream Disturbance

Babu

Anish

2020

JAFM

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“…A similar effect is observed on rotor endwalls with changes in the cavity purge flow. 15 The proxy model discussed in this paper does not model the dynamics of the endwall flow in a way that could capture regime shifts. If applied in environments of this type, it is possible that a local optimum could be found on one side or the other of a Figure 18.…”

Section: Thomas and Povey 6 And Ornano And Povey 14 )mentioning

confidence: 99%

Combined scalar tracking, computational fluid dynamics, and multi-objective genetic algorithm method to accelerate optimization of film cooling systems

Ornano

Povey

2020

Proceedings of the Institution of Mechanical Engineers, Part A:

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This paper presents a method to significantly accelerate optimization of film cooling systems. The method combines high-fidelity computational fluid dynamics with scalar tracking implemented, a proxy model (linear superposition model) initialized with the computational fluid dynamics solution, and a multi-objective evolutionary algorithm approach. The proposed method is structured as follows: the computational fluid dynamics solution is used to predict the (generally complex) flow domain for the film cooling system; the scalar tracking method identifies the contributions of individual holes to an overall cooling effectiveness distribution by associating a unique passive scalar variable to the flow associated with each hole, and solving an additional advection–diffusion (scalar transport) equation; the proxy model is a (generally linear) superposition model implemented – for example – in Matlab, which inherits the scalar values from the computational fluid dynamics solution, and allows extrapolation of solutions to new design points as part of an optimization process; the optimization process is handled with a multi-objective evolutionary algorithm approach which iterates the proxy model to optimize for a defined objective function. The process works with inner and outer convergence loops. The inner convergence loop is the multi-objective evolutionary algorithm interfacing with the proxy model, which achieves convergence against a design target. At the end of each inner loop cycle, a high-fidelity computational fluid dynamics simulation is run, and this is used to recalibrate the proxy model. Convergence for a given objective function is typically achieved with six outer-loop iterations (high-fidelity computational fluid dynamics runs) and 10,000 inner-loop iterations per outer-loop iteration. The significant advantage of the proposed method is that for certain optimization problems, the computational cost can be reduced by several orders of magnitude, replacing thousands of high-fidelity computational fluid dynamics runs with approximately six computational fluid dynamics runs. The process is demonstrated by applying the optimization method to the film cooling of a flat plate. In our example we have an objective function which maximizes the component life (related to the difference from an arbitrary target temperature distribution) and minimizes the mixing loss introduced by the films. The flow environment was moderately compressible. The optimization converged after six computational fluid dynamics runs. A 30% reduction in mixing loss, a 11% increase in component life, and a 30% reduction in cooling mass flow rate were achieved. The advantages and limitations of the proposed method are also discussed in detail.

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“…As an example, the study by Cui and Tucker [16] addresses endwall flow and the interaction with the cavity purge flow by LES. Although in LPT endwalls are not as important as in HPTs, their impact on performance is quite significant, especially for the front stages of an aircraft engine multistage LPT.…”

Section: Low-pressure Turbinementioning

confidence: 99%

The Current State of High-Fidelity Simulations for Main Gas Path Turbomachinery Components and Their Industrial Impact

Sandberg

Michelassi²

2019

Flow Turbulence Combust

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Over the past two decades high-fidelity simulations have become feasible for most main gas path turbomachinery components. This paper introduces the key challenges of simulating and modelling turbomachinery flows and presents an overview of possible simulation strategies. A comprehensive overview is given of which particular design challenges have to date been addressed by high-fidelity simulations, with a particular focus on high-pressure and centrifugal compressors, and high-pressure and low-pressure turbines. Recommendations are provided for how quality and accuracy can be ensured for high-fidelity simulations, using direct numerical simulations of a low-pressure turbine as a case study. It is argued that industrial impact from high-fidelity simulations can be achieved in two ways, either by conducting design-of-experiment-like studies that can provide designers with insight into certain physical mechanisms and phenomena, or by helping mature and improve lower-order models. The latter is discussed with particular emphasis on recent advances in machine learning for model assessment and improvement, and the potential of one selected data-driven approach is demonstrated on predictions of wake mixing for low-pressure and high-pressure turbines.

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Numerical Study of Purge and Secondary Flows in a Low Pressure Turbine

Cited by 10 publications

References 16 publications

Computational Predictions of Velocity Ratio and Ejection Angle on Purge Flow in a Linear Turbine Cascade with Upstream Disturbance

Computational Predictions of Velocity Ratio and Ejection Angle on Purge Flow in a Linear Turbine Cascade with Upstream Disturbance

Combined scalar tracking, computational fluid dynamics, and multi-objective genetic algorithm method to accelerate optimization of film cooling systems

The Current State of High-Fidelity Simulations for Main Gas Path Turbomachinery Components and Their Industrial Impact

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