The compound bowing design in a highly loaded linear cascade with large turning angle

2020 ◽  
Vol 234 (16) ◽  
pp. 2323-2336
Author(s):  
Xingxu Xue ◽  
Songtao Wang ◽  
Lei Luo ◽  
Xun Zhou
Keyword(s):  
Numerical Simulation ◽  
Reynolds Number ◽  
Pressure Gradient ◽  
Side Effect ◽  
Adverse Pressure Gradient ◽  
Suction Surface ◽  
Turning Angle ◽  
Linear Cascade ◽  
Velocity Triangle ◽  
Highly Loaded

Numerical simulation was carried out to study the influences of blade-bowing designs based on a highly loaded cascade with large turning angle, while the compound bowing design showed much lower endwall loss than the conventional design in this study. Generally, it showed that the increased turning angle would strengthen the adverse pressure gradient on the suction surface, so the side effect of negative blade bowing angle would be enhanced because of the reduced flow filed stability near suction–endwall corner. However, the positive corner bowing angle that applied in the compound bowing design would enhance the flow field stability near the suction–endwall corner by adjusting spanwise pressure gradient and velocity triangle, so the side effect of negative blade bowing angle would be suppressed and lead to weaker secondary flow. In detail, the blade bowing angle (as well as the corner bowing angle in the conventional bowed cascades) was varied from −5° to −30° in this study, while the reductions of the loss coefficient in the compound bowed cascades were about 0.662.16 times higher (the absolute differences were about 0.0067 0.0097) than the corresponding conventional bowed cascades. Moreover, the Reynolds number and Mach number at the outlet plane were kept at 2.4 × 105 and 0.6, respectively, during the bowing design to ensure the comparability.

Production and Development of Secondary Flows and Losses in Two Types of Straight Turbine Cascades: Part 2—A Rotor Case

1987 ◽  
Vol 109 (2) ◽  
pp. 194-200 ◽  
Author(s):  
A. Yamamoto
Keyword(s):  
Pressure Gradient ◽  
Production Process ◽  
Experimental Analysis ◽  
Significant Contribution ◽  
Adverse Pressure Gradient ◽  
Secondary Flows ◽  
Suction Surface ◽  
Turning Angle ◽  
Detailed Mechanism ◽  
Turbine Cascades

Part 1 of this paper [1] presents the detailed mechanism of secondary flows and the associated losses occurring within a straight stator cascade with a relatively low turning angle of about 65 deg. The significant contribution of secondary flows on the loss production process was shown only near the blade suction surface downstream from the cascade throat (Z/Cax = 0.74) in which regional flows decelerated due to adverse pressure gradient. In the second part, the same experimental analysis is applied to a straight rotor cascade with a much larger turning angle of 102 deg. Flow surveys were made at 12 traverse planes located throughout the rotor cascade. The larger turning results in a similar but much stronger contribution of the secondary flows to the loss developing mechanism. Evolution of overall loss starts quite early within the cascade, and the rate of the loss growth is much larger in the rotor case than in the stator case.

scholarly journals Direct numerical simulation of a self-similar adverse pressure gradient turbulent boundary layer at the verge of separation

2017 ◽  
Vol 829 ◽  
pp. 392-419 ◽  
Author(s):  
V. Kitsios ◽  
A. Sekimoto ◽  
C. Atkinson ◽  
J. A. Sillero ◽  
G. Borrell ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Boundary Layer ◽  
Reynolds Number ◽  
Direct Numerical Simulation ◽  
Pressure Gradient ◽  
Adverse Pressure Gradient ◽  
Streamwise Velocity ◽  
Far Field ◽  
Self Similar ◽  
The Mean

The statistical properties are presented for the direct numerical simulation of a self-similar adverse pressure gradient (APG) turbulent boundary layer (TBL) at the verge of separation. The APG TBL has a momentum thickness-based Reynolds number range from $Re_{\unicode[STIX]{x1D6FF}_{2}}=570$ to 13 800, with a self-similar region from $Re_{\unicode[STIX]{x1D6FF}_{2}}=10\,000$ to 12 300. Within this domain the average non-dimensional pressure gradient parameter $\unicode[STIX]{x1D6FD}=39$, where for a unit density $\unicode[STIX]{x1D6FD}=\unicode[STIX]{x1D6FF}_{1}P_{\!e}^{\prime }/\unicode[STIX]{x1D70F}_{w}$, with $\unicode[STIX]{x1D6FF}_{1}$ the displacement thickness, $\unicode[STIX]{x1D70F}_{w}$ the mean shear stress at the wall and $P_{\!e}^{\prime }$ the far-field pressure gradient. This flow is compared with previous zero pressure gradient and mild APG TBL ($\unicode[STIX]{x1D6FD}=1$) results of similar Reynolds number. All flows are generated via the direct numerical simulation of a TBL on a flat surface with far-field boundary conditions tailored to apply the desired pressure gradient. The conditions for self-similarity, and the appropriate length and velocity scales, are derived. The mean and Reynolds stress profiles are shown to collapse when non-dimensionalised on the basis of these length and velocity scales. As the pressure gradient increases, the extent of the wake region in the mean streamwise velocity profiles increases, whilst the extent of the log-layer and viscous sublayer decreases. The Reynolds stress, production and dissipation profiles of the APG TBL cases exhibit a second outer peak, which becomes more pronounced and more spatially localised with increasing pressure gradient. This outer peak is located at the point of inflection of the mean velocity profiles, and is suggestive of the presence of a shear flow instability. The maximum streamwise velocity variance is located at a wall normal position of $\unicode[STIX]{x1D6FF}_{1}$ of spanwise wavelength of $2\unicode[STIX]{x1D6FF}_{1}$. In summary as the pressure gradient increases the flow has properties less like a zero pressure gradient TBL and more akin to a free shear layer.

Production and Development of Secondary Flows and Losses Within Two Types of Straight Turbine Cascades: Part 2 — A Rotor Case

1986 ◽  
Author(s):  
A. Yamamoto
Keyword(s):  
Pressure Gradient ◽  
Production Process ◽  
Experimental Analysis ◽  
Significant Contribution ◽  
Adverse Pressure Gradient ◽  
Secondary Flows ◽  
Suction Surface ◽  
Turning Angle ◽  
Detailed Mechanism ◽  
Turbine Cascades

Part 1 of this paper[1] presented the detailed mechanism of secondary flows and the associated losses occurring within a straight stator cascade with a relatively low turning angle of about 65°. Significant contribution of secondary flows on the loss production process was shown only near the blade suction surface downstream from the cascade throat (Z/Cax=0.74) in which region flows decelerated due to adverse pressure gradient. In the second part, the same experimental analysis was applied to a straight rotor cascade with a much larger turning-angle of 102°. Flow surveys were made at twelve traverse planes located throughout the rotor cascade. The larger turning results in a similar but much stronger contribution of the secondary flows on the loss developing mechanism. Evolution of overall loss starts quite early within the cascade, and the rate of the loss growth is much larger in the rotor case than in the stator case.

Pressure gradient effects on the large-scale structure of turbulent boundary layers

2013 ◽  
Vol 715 ◽  
pp. 477-498 ◽  
Author(s):  
Zambri Harun ◽  
Jason P. Monty ◽  
Romain Mathis ◽  
Ivan Marusic
Keyword(s):  
Boundary Layer ◽  
Reynolds Number ◽  
Pressure Gradient ◽  
Boundary Layers ◽  
Amplitude Modulation ◽  
Large Scale ◽  
Outer Region ◽  
Adverse Pressure Gradient ◽  
Turbulent Boundary Layers ◽  
Small Scale

AbstractResearch into high-Reynolds-number turbulent boundary layers in recent years has brought about a renewed interest in the larger-scale structures. It is now known that these structures emerge more prominently in the outer region not only due to increased Reynolds number (Metzger & Klewicki, Phys. Fluids, vol. 13(3), 2001, pp. 692–701; Hutchins & Marusic, J. Fluid Mech., vol. 579, 2007, pp. 1–28), but also when a boundary layer is exposed to an adverse pressure gradient (Bradshaw, J. Fluid Mech., vol. 29, 1967, pp. 625–645; Lee & Sung, J. Fluid Mech., vol. 639, 2009, pp. 101–131). The latter case has not received as much attention in the literature. As such, this work investigates the modification of the large-scale features of boundary layers subjected to zero, adverse and favourable pressure gradients. It is first shown that the mean velocities, turbulence intensities and turbulence production are significantly different in the outer region across the three cases. Spectral and scale decomposition analyses confirm that the large scales are more energized throughout the entire adverse pressure gradient boundary layer, especially in the outer region. Although more energetic, there is a similar spectral distribution of energy in the wake region, implying the geometrical structure of the outer layer remains universal in all cases. Comparisons are also made of the amplitude modulation of small scales by the large-scale motions for the three pressure gradient cases. The wall-normal location of the zero-crossing of small-scale amplitude modulation is found to increase with increasing pressure gradient, yet this location continues to coincide with the large-scale energetic peak wall-normal location (as has been observed in zero pressure gradient boundary layers). The amplitude modulation effect is found to increase as pressure gradient is increased from favourable to adverse.

The Effective Positions to Inject Water Into the Cascade of Compressor

2012 ◽  
Author(s):  
Jie Wang ◽  
Qun Zheng ◽  
Lanxin Sun ◽  
Mingcong Luo
Keyword(s):  
Kinetic Energy ◽  
Total Pressure ◽  
Lower Energy ◽  
Water Injection ◽  
Adverse Pressure Gradient ◽  
Compressor Cascade ◽  
Suction Surface ◽  
Pressure Losses ◽  
Ansys Cfx ◽  
Highly Loaded

Generally, droplets are injected into air at inlet or interstage of a compressor. However, both cases did not consider how to utilize the kinetic energy of these moving droplets. Under the adverse pressure gradient of compressor, the lower energy fluids of blade surfaces and endwalls boundary layers would accumulate and separate. Kinetic droplets could accelerate the lower energy fluids and eliminate the separation. This paper mainly investigate the effective positions where to inject water and how to utilize the droplets’ kinetic energy. Four different injecting positions, which located on the suction surface and endwall, are chosen. The changes of vortexes in the compressor cascade are discussed carefully. In addition, the influences of water injection on temperature, total pressure losses and Mach number are analyzed. Numerical simulations are performed for a highly loaded compressor cascade with ANSYS CFX software.

Numerical Performance of Transition Models in Different Turbomachinery Flow Conditions: A Comparative Study

2000 ◽  
Author(s):  
Jiasen Hu ◽  
Torsten H. Fransson
Keyword(s):  
Reynolds Number ◽  
Pressure Gradient ◽  
Numerical Study ◽  
Adverse Pressure Gradient ◽  
Navier Stokes ◽  
Test Cases ◽  
Pressure Gradients ◽  
Flow Conditions ◽  
Transition Models ◽  
High Reynolds

A numerical study has been performed to compare the overall performance of three transition models when used with an industrial Navier-Stokes solver. The three models investigated include two experimental correlations and an integrated eN method. Twelve test cases in realistic turbomachinery flow conditions have been calculated. The study reveals that all the three models can work numerically well with an industrial Navier-Stokes code, but the prediction accuracy of the models depends on flow conditions. In general, all the three models perform comparably well to predict the transition in weak or moderate adverse pressure-gradient regions. The two correlations have the merit if the transition starts in strong favorable pressure-gradient region under high Reynolds number condition. But only the eN method works well to predict the transition controlled by strong adverse pressure gradients. The three models also demonstrate different capabilities to model the effects of turbulence intensity and Reynolds number.

Governing Parameters of Adverse Pressure Gradient Turbulent Boundary Layers

2018 ◽  
Author(s):  
Yvan Maciel ◽  
Tie Wei ◽  
Ayse G. Gungor ◽  
Mark P. Simens
Keyword(s):  
Boundary Layer ◽  
Reynolds Number ◽  
Pressure Gradient ◽  
Boundary Layers ◽  
Outer Region ◽  
Adverse Pressure Gradient ◽  
Turbulent Boundary Layers ◽  
Inertial Parameter ◽  
Velocity Scale ◽  
Gradient Parameter

We perform a careful nondimensional analysis of the turbulent boundary layer equations in order to bring out, without assuming any self-similar behaviour, a consistent set of nondimensional parameters characterizing the outer region of turbulent boundary layers with arbitrary pressure gradients. These nondimensional parameters are a pressure gradient parameter, a Reynolds number (different from commonly used ones) and an inertial parameter. They are obtained without assuming a priori the outer length and velocity scales. They represent the ratio of the magnitudes of two types of forces in the outer region, using the Reynolds shear stress gradient (apparent turbulent force) as the reference force: inertia to apparent turbulent forces for the inertial parameter, pressure to apparent turbulent forces for the pressure gradient parameter and apparent turbulent to viscous forces for the Reynolds number. We determine under what conditions they retain their meaning, depending on the outer velocity scale that is considered, with the help of seven boundary layer databases. We find the impressive result that if the Zagarola-Smits velocity is used as the outer velocity scale, the streamwise evolution of the three ratios of forces in the outer region can be accurately followed with these non-dimensional parameters in all these flows — not just the order of magnitude of these ratios. This cannot be achieved with three other outer velocity scales commonly used for pressure gradient turbulent boundary layers. Consequently, the three new nondimensional parameters, when expressed with the Zagarola-Smits velocity, can be used to follow — in a global sense — the streamwise evolution of the stream-wise mean momentum balance in the outer region. This study provides a clear and consistent framework for the analysis of the outer region of adverse-pressure-gradient turbulent boundary layers.

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