Turbulence Measurements Downstream of a Turbine Cascade at Different Incidence Angles and Pitch-Chord Ratios

1993 ◽  
Author(s):  
Vincenzo Dossena ◽  
Antonio Perdichizzi ◽  
Marina Ubaldi ◽  
Pietro Zunino
Keyword(s):  
Turbulent Flow ◽  
Reynolds Stress ◽  
Incidence Angle ◽  
Three Dimensional ◽  
Turbulence Models ◽  
Turbine Cascade ◽  
Mean Flow ◽  
Flow Measurements ◽  
Flow Features ◽  
Turbulent Flow Structure

An experimental investigation on a linear turbine cascade has been carried out to study the effects induced by incidence angle and pitch-chord ratio variations on the three-dimensional turbulent flow downstream of the cascade. Previous mean flow measurements have shown how these parameters influence the energy losses and the secondary velocity field. Now detailed hot wire measurements have been performed on a plane located at 22 per cent of an axial chord downstream of the trailing edge, in order to determine the distribution of all the six Reynolds stress tensor components, for three incidence conditions (i = −30, 0, +30 deg) and for three pitch-chord ratios (s/c = 0.58, 0.72, 0.87). Significant changes of the turbulent flow structure, interesting magnitude and distribution of the Reynolds stress components, have been observed for all the considered test conditions. The analysis of the results shows the correlation between the mean flow features and the turbulent quantities and the relationship between the energy loss production and the blade loading variation. The presented data are also suitable for assessing the behaviour of turbulence models in complex 3D flows, on design and off-design conditions.

Highly resolved experimental results of the separated flow in a channel with streamwise periodic constrictions

2016 ◽  
Vol 796 ◽  
pp. 257-284 ◽  
Author(s):  
Christian J. Kähler ◽  
Sven Scharnowski ◽  
Christian Cierpka
Keyword(s):  
Turbulent Flow ◽  
Flow Separation ◽  
Flow Direction ◽  
Separated Flow ◽  
Mean Flow ◽  
Complex Flow ◽  
Flow Measurements ◽  
Flow Features ◽  
Wall Flow ◽  
Near Wall

The understanding and accurate prediction of turbulent flow separation on smooth surfaces is still a challenging task because the separation and the reattachment locations are not fixed in space and time. Consequently, reliable experimental data are essential for the validation of numerical flow simulations and the characterization and analysis of the complex flow physics. However, the uncertainty of the existing near-wall flow measurements make a precise analysis of the near-wall flow features, such as separation/reattachment locations and other predicted near-wall flow features which are under debate, often impossible. Therefore, the periodic hill experiment at TU Munich (ERCOFTAC test case 81) was repeated using high resolution particle image velocimetry and particle tracking velocimetry. The results confirm the strong effect of the spatial resolution on the near-wall flow statistics. Furthermore, it is shown that statistically stable values of the turbulent flow variables can only be obtained for averaging times which are challenging to realize with highly resolved large eddy simulation and direct numerical simulation techniques. Additionally, the analysis implies that regions of correlated velocity fluctuations with rather uniform streamwise momentum exist in the flow. Their size in the mean flow direction can be larger than the hill spacing. The possible impact of the correlated turbulent motion on the wake region is discussed, as this interaction might be important for the understanding and control of the flow separation dynamics on smooth bodies.

scholarly journals Characterization of Model-Based Uncertainties in Incompressible Turbulent Flows by Machine Learning

2018 ◽  
Author(s):  
Mustafa Usta ◽  
Ali Tosyali
Keyword(s):  
Machine Learning ◽  
Turbulent Flows ◽  
Three Dimensional ◽  
Turbulence Models ◽  
Machine Learning Algorithms ◽  
Mean Flow ◽  
Flow Properties ◽  
Significant Discrepancy ◽  
Model Based ◽  
Flow Features

This work determines the inaccuracy of using Reynolds averaged Navier Stokes (RANS) turbulence models in transition to turbulent flow regimes by predicting the model-based discrepancies between RANS and large eddy simulation (LES) models. Then, it incorporates the capabilities of machine learning algorithms to characterize the discrepancies which are defined as a function of mean flow properties of RANS simulations. First, three-dimensional CFD simulations using k-omega Shear Stress Transport (SST) and dynamic one-equation subgrid-scale models are conducted in a wall-bounded channel containing a cylinder for RANS and LES, respectively, to identify the turbulent kinetic energy discrepancy. Second, several flow features such as viscosity ratio, wall-distance based Reynolds number, and vortex stretching are calculated from the mean flow properties of RANS. Then the discrepancy is regressed on these flow features using the Random Forests regression algorithm. Finally, the discrepancy of the test flow is predicted using the trained algorithm. The results reveal that a significant discrepancy exists between RANS and LES simulations, and ML algorithm successfully predicts the increased model uncertainties caused by the employment of k-omega SST turbulence model for transitional fluid flows.

Measurements and Predictions of a Highly Turbulent Flowfield in a Turbine Vane Passage

2000 ◽  
Vol 122 (4) ◽  
pp. 666-676 ◽  
Author(s):  
R. W. Radomsky ◽  
K. A. Thole
Keyword(s):  
Kinetic Energy ◽  
Turbulent Flow ◽  
Gas Turbine ◽  
Turbulent Kinetic Energy ◽  
Reynolds Stress ◽  
Complex Geometry ◽  
Turbulence Models ◽  
Reynolds Stress Model ◽  
Stress Model ◽  
Mean Flow

As highly turbulent flow passes through downstream airfoil passages in a gas turbine engine, it is subjected to a complex geometry designed to accelerate and turn the flow. This acceleration and streamline curvature subject the turbulent flow to high mean flow strains. This paper presents both experimental measurements and computational predictions for highly turbulent flow as it progresses through a passage of a gas turbine stator vane. Three-component velocity fields at the vane midspan were measured for inlet turbulence levels of 0.6%, 10%, and 19.5%. The turbulent kinetic energy increased through the passage by 130% for the 10% inlet turbulence and, because the dissipation rate was higher for the 19.5% inlet turbulence, the turbulent kinetic energy increased by only 31%. With a mean flow acceleration of five through the passage, the exiting local turbulence levels were 3% and 6% for the respective 10% and 19.5% inlet turbulence levels. Computational RANS predictions were compared with the measurements using four different turbulence models including the k-ε, Renormalization Group (RNG) k-ε, realizable k-ε, and Reynolds stress model. The results indicate that the predictions using the Reynolds stress model most closely agreed with the measurements as compared with the other turbulence models with better agreement for the 10% case than the 19.5% case. [S0098-2202(00)00804-X]

An explicit algebraic Reynolds stress model for incompressible and compressible turbulent flows

2000 ◽  
Vol 403 ◽  
pp. 89-132 ◽  
Author(s):  
STEFAN WALLIN ◽  
ARNE V. JOHANSSON
Keyword(s):  
Turbulent Flows ◽  
Reynolds Stress ◽  
Compressible Flows ◽  
Three Dimensional ◽  
Turbulence Models ◽  
Reynolds Stress Model ◽  
Reynolds Stresses ◽  
Mean Flow ◽  
New Developments ◽  
The Individual

Some new developments of explicit algebraic Reynolds stress turbulence models (EARSM) are presented. The new developments include a new near-wall treatment ensuring realizability for the individual stress components, a formulation for compressible flows, and a suggestion for a possible approximation of diffusion terms in the anisotropy transport equation. Recent developments in this area are assessed and collected into a model for both incompressible and compressible three-dimensional wall-bounded turbulent flows. This model represents a solution of the implicit ARSM equations, where the production to dissipation ratio is obtained as a solution to a nonlinear algebraic relation. Three-dimensionality is fully accounted for in the mean flow description of the stress anisotropy. The resulting EARSM has been found to be well suited to integration to the wall and all individual Reynolds stresses can be well predicted by introducing wall damping functions derived from the van Driest damping function. The platform for the model consists of the transport equations for the kinetic energy and an auxiliary quantity. The proposed model can be used with any such platform, and examples are shown for two different choices of the auxiliary quantity.

scholarly journals Three-Dimensional Navier-Stokes Computation of Turbine Nozzle Flow With Advanced Turbulence Models

1995 ◽  
Author(s):  
J. Luo ◽  
B. Lakshminarayana
Keyword(s):  
Reynolds Stress ◽  
Three Dimensional ◽  
Turbulence Models ◽  
Reynolds Stress Model ◽  
Navier Stokes ◽  
Nozzle Flow ◽  
Stress Model ◽  
Mean Flow ◽  
The Mean ◽  
Algebraic Reynolds Stress Model

A three-dimensional Navier-Stokes procedure has been used to compute the three-dimensional viscous flow through the turbine nozzle passage of a single stage turbine. A low Reynolds number k-ε model and a zonal k-ε/ARSM (algebraic Reynolds stress model) are utilized for turbulence closure. The algebraic Reynolds stress model is used only in the endwall region to represent the anisotropy of turbulence. A four-stage Runge-Kutta scheme is used for time-integration of both the mean-flow and the turbulence transport equations. For the turbine nozzle flow, comprehensive comparisons between the predictions and the experimental data obtained at Penn State show that most features of the vortex-dominated endwall flow, as well as nozzle wake structure, have been captured well by the numerical procedure. An assessment of the performance of the turbulence models has been carried out The two models are found to provide similar predictions for the mean flow parameters, although slight improvement in the prediction of some secondary flow quantities has been obtained by the ARSM model.

Prediction of Developing Turbulent Flow in a 90° Curved Duct Using Linear and Nonlinear Low-Re k-ε Models

Volume 1 ◽  
2004 ◽  
Author(s):  
M. Raisee ◽  
H. Alemi ◽  
H. Iacovides
Keyword(s):  
Turbulent Flow ◽  
Pressure Coefficient ◽  
Three Dimensional ◽  
Turbulence Models ◽  
Main Stream ◽  
Local Pressure ◽  
Flow Measurements ◽  
Numerical Predictions ◽  
Flow Development ◽  
Curved Section

This paper reports the outcome of applying two different low-Re number eddy-viscosity models to resolve the complex three-dimensional motion that arises in turbulent flow in a square cross-section duct passing around a 90° bend. Flow computations have been obtained using a three-dimensional, non-orthogonal flow solver. For modeling of turbulence, the Launder and Sharma low-Re k–ε model and a recently modified version of nonlinear low-Re k–ε model that have been shown to be suitable for flow and thermal predictions in re-circulating and impinging jet flows, have been employed. A bounded version of the QUICK scheme was used for the approximation of convection in all transport equations. The numerical predictions are validated through comparisons with the reported flow measurements and are used to explain how the curvature influences the flow development. The results of the present investigation indicate that the curvature induces a strong secondary flow in the curved section of the duct. The secondary motion also persists downstream of the bend, although it slowly disappears with the main stream development. At the entrance of the curved section, the curvature alters the flow development by displacing the fluid towards the convex (inner) wall. Comparisons of the predicted stream-wise and cross-stream velocity components with the measured data indicate that both turbulence models employed in the present study can produce reasonable predictions, although the non-linear model predictions are generally closer to the measurements. Both turbulence models successfully reproduce the distribution as well as the levels of the local pressure coefficient in the curved section of the duct.

Three-Dimensional Navier–Stokes Computation of Turbine Nozzle Flow With Advanced Turbulence Models

1997 ◽  
Vol 119 (3) ◽  
pp. 516-530 ◽  
Author(s):  
J. Luo ◽  
B. Lakshminarayana
Keyword(s):  
Reynolds Stress ◽  
Three Dimensional ◽  
Turbulence Models ◽  
Reynolds Stress Model ◽  
Navier Stokes ◽  
Nozzle Flow ◽  
Stress Model ◽  
Mean Flow ◽  
The Mean ◽  
Algebraic Reynolds Stress Model

A three-dimensional Navier–Stokes procedure has been used to compute the three-dimensional viscous flow through the turbine nozzle passage of a single-stage turbine. A low-Reynolds-number k–ε model and a zonal k-ε/ARSM (algebraic Reynolds stress model) are utilized for turbulence closure. The algebraic Reynolds stress model is used only in the endwall region to represent the anisotropy of turbulence. A four-stage Runge–Kutta scheme is used for time integration of both the mean-flow and the turbulence transport equations. For the turbine nozzle flow, comprehensive comparisons between the predictions and the experimental data obtained at Penn State show that most features of the vortex-dominated endwall flow, as well as nozzle wake structure, have been captured well by the numerical procedure. An assessment of the performance of the turbulence models has been carried out. The two models are found to provide similar predictions for the mean flow parameters, although slight improvement in the prediction of some secondary flow quantities has been obtained by the ARSM model.

scholarly journals Incidence Angle and Pitch-Chord Effects on Secondary Flows Downstream of a Turbine Cascade

1992 ◽  
Author(s):  
A. Perdichizzi ◽  
V. Dossena
Keyword(s):  
Flow Field ◽  
Secondary Flow ◽  
Incidence Angle ◽  
Three Dimensional ◽  
Secondary Flows ◽  
Pressure Probe ◽  
Turbine Cascade ◽  
Oil Flow ◽  
Secondary Velocity ◽  
Secondary Flow Field

This paper describes the results of an experimental investigation of the three-dimensional flow downstream of a linear turbine cascade at off-design conditions. The tests have been carried out for five incidence angles from −60 to +35 degrees, and for three pitch-chord ratios: s/c = 0.58,0.73,0.87. Data include blade pressure distributions, oil flow visualizations, and pressure probe measurements. The secondary flow field has been obtained by traversing a miniature five hole probe in a plane located at 50% of an axial chord downstream of the trailing edge. The distributions of local energy loss coefficients, together with vorticity and secondary velocity plots show in detail how much the secondary flow field is modified both by incidence and cascade solidity variations. The level of secondary vorticity and the intensity of the crossflow at the endwall have been found to be strictly related to the blade loading occurring in the blade entrance region. Heavy changes occur in the spanwise distributions of the pitch averaged loss and of the deviation angle, when incidence or pitch-chord ratio is varied.

Numerical Prediction of Flow in a Nuclear Fuel Bundle With Various Turbulence Models

2002 ◽  
Author(s):  
Wang Kee In ◽  
Dong Seok Oh ◽  
Tae Hyun Chun
Keyword(s):  
Turbulent Flow ◽  
Nuclear Fuel ◽  
Turbulence Models ◽  
Convective Transport ◽  
Stress Model ◽  
Convergence Criteria ◽  
Mean Flow ◽  
Numerical Predictions ◽  
Viscosity Models ◽  
Fuel Bundle

The numerical predictions using the standard and RNG k–ε eddy viscosity models, differential stress model (DSM) and algebraic stress model (ASM) are examined for the turbulent flow in a nuclear fuel bundle with the mixing vane. The hybrid (first-order) and curvature-compensated convective transport (CCCT) schemes were used to examine the effect of the differencing scheme for the convection term. The CCCT scheme was found to more accurately predict the characteristics of turbulent flow in the fuel bundle. There is a negligible difference in the prediction performance between the standard and RNG k-ε models. The calculation using ASM failed in meeting the convergence criteria. DSM appeared to more accurately predict the mean flow velocities as well as the turbulence parameters.

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