Impact of Geometric Variability on Axial Compressor Performance

Garzón, Víctor E.; Darmofal, David L.

doi:10.1115/gt2003-38130

Cited by 25 publications

(4 citation statements)

References 8 publications

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“…and Darmofal [47] used 150 blade surface measurements in their probabilistic approach to quantify the impact of geometric variability on compressor aerodynamic performance. However, since high-fidelity data is computationally very expensive, such a situation can easily be encountered in an engineering framework.…”

Section: Collocation Points For Uq Studymentioning

confidence: 99%

A hybrid approach combining DNS and RANS simulations to quantify uncertainties in turbulence modelling

Voet

Ahlfeld

Gaymann

et al. 2021

Applied Mathematical Modelling

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Uncertainty quantification (UQ) has recently become an important part of the design process of countless engineering applications. However, up to now in computational fluid dynamics (CFD) the errors introduced by the turbulent viscosity models in Reynolds-Averaged Navier Stokes (RANS) models have often been neglected in UQ studies. Although Direct Numerical Simulations (DNS) are physically correct, obtaining a large enough set of DNS data for UQ studies is currently computationally intractable.UQ based only on RANS simulations or on DNS often leads to physical and statistical inaccuracies in the output probability distribution functions (PDF). Therefore, three hybrid methods combining both RANS simulations and DNS to perform non-intrusive UQ are suggested in this work. Low-fidelity RANS simulations and high-fidelity DNS are combined to give an approximation of an output PDF using the advantages of both data sets: the physical accuracy via the DNS and the statistical accuracy via the RANS simulations. The hybrid methods are applied to the flow over 2D periodically arranged hills. It is shown that the Gaussian CoKriging (GCK) method is the best hybrid method and that a non-intrusive hybrid UQ approach combining both DNS and RANS simulations is possible, with both physically more accurate and statistically better PDF.

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Section: Collocation Points For Uq Studymentioning

confidence: 99%

A hybrid approach combining DNS and RANS simulations to quantify uncertainties in turbulence modelling

Voet

Ahlfeld

Gaymann

et al. 2021

Applied Mathematical Modelling

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“…MISES is a steady 2-D coupled Euler boundary layer solver developed by Mark Drela. The program is well-documented and validated, and has a wide application in both the fields of internal and external aerodynamics, for example by Garzon & Darmofal (2003) to study the impact of geometric variability on compressor performance. The boundary layers were considered to be fully turbulent.…”

Section: Misesmentioning

confidence: 99%

The Effect of Reaction on Compressor Performance

Chana

Miller

2022

Journal of Turbomachinery

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Reaction is the fundamental parameter by which the asymmetry of the velocity triangle of a stage is set. Little is understood about the effect that reaction has on either the efficiency or the operating range of a compressor. A particular difficulty in understanding the effect of reaction is that the rotor and stator have a natural asymmetry caused by the centrifugal effects in the rotor boundary layer being much larger than that in the stator boundary layer. In this paper a novel approach has been taken: McKenzie's ‘linear repeating stage’ concept is used to remove the centrifugal effects. The centrifugal effects are then reintroduced as a body force. This allows the velocity triangle effect and centrifugal force effect to be decoupled. The paper shows the surprising result that, depending on how the solidity is set, a 50% reaction stage can either result in the maximum, or the minimum, profile loss. When the centrifugal effects are removed, 50% reaction is shown to minimise endwall loss, maximise stage efficiency and maximise operating range. When the centrifugal effects are reintroduced, the compressor with the maximum design efficiency is found to rise in reaction by 5% (from 50% reaction to 55% reaction) and the compressor with the maximum operating range is found to rise in reaction by 15% (from 50% reaction to 65% reaction).

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“…Many researchers have shown that compressor blades can be very sensitive to variations in geometry [56][57][58]. Probabilistic analysis has shown substantial degradation in the performance of compressor blades in the presence of manufacturing variations, errors, and tolerances [59,60].…”

Section: Process Capability Datamentioning

confidence: 99%

Robust design using Bayesian Monte Carlo

Kumar

Nair

Keane

et al. 2007

Numerical Meth Engineering

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SUMMARYIn this paper, we propose an efficient strategy for robust design based on Bayesian Monte Carlo simulation. Robust design is formulated as a multiobjective problem to allow explicit trade-off between the mean performance and variability. The proposed method is applied to a compressor blade design in the presence of manufacturing uncertainty. Process capability data are utilized in conjunction with a parametric geometry model for manufacturing uncertainty quantification. High-fidelity computational fluid dynamics simulations are used to evaluate the aerodynamic performance of the compressor blade. A probabilistic analysis for estimating the effect of manufacturing variations on the aerodynamic performance of the blade is performed and a case for the application of robust design is established. The proposed approach is applied to robust design of compressor blades and a selected design from the final Pareto set is compared with an optimal design obtained by minimizing the nominal performance. The selected robust blade has substantial improvement in robustness against manufacturing variations in comparison with the deterministic optimal blade. Significant savings in computational effort using the proposed method are also illustrated.

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Impact of Geometric Variability on Axial Compressor Performance

Cited by 25 publications

References 8 publications

A hybrid approach combining DNS and RANS simulations to quantify uncertainties in turbulence modelling

A hybrid approach combining DNS and RANS simulations to quantify uncertainties in turbulence modelling

The Effect of Reaction on Compressor Performance

Robust design using Bayesian Monte Carlo

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