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Results for “BOUNDARY LAYER, TURBULENT - EFFECT OF PRESSURE GRADIENT”

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At least 19 records

Implicit Large-Eddy Simulations of Zero-Pressure Gradient, Turbulent Boundary Layer

A set of direct simulations of zero-pressure gradient, turbulent boundary layer flows are conducted using various span widths (62-630 wall units), to document their influence on the generated turbulence. The FDL3DI code that solves compressible Navier-Stokes equations using high-order compact-difference scheme and filter, with the standard recycling/rescaling method of turbulence generation, is used. Results are analyzed at two different Re values (500 and 1,400), and compared with spectral DNS data. They show that a minimum span width is required for the mere initiation of numerical turbulence. Narrower domains ((is) less than 100 w.u.) result in relaminarization. Wider spans ((is) greater than 600 w.u.) are required for the turbulent statistics to match reference DNS. The upper-wall boundary condition for this setup spawns marginal deviations in the mean velocity and Reynolds stress profiles, particularly in the buffer region.

Turblent boundary layer↗

An experimental study of the properties of surface pressure fluctuations in strong adverse pressure gradient turbulent boundary layers

Experimental data were obtained on blade self-noise generation by strong adverse-pressure-gradient attached boundary layers and by separated turbulent boundary layers that accompany stall. Two microphones were calibrated, placed in plastic housing, and installed in a wind tunnel where observations of acoustic and turbulent signals permitted decomposition of the surface pressure fluctuation signals into the propagated acoustic part and the turbulent-flow generated portion. To determine the convective wave speed of the turbulent contributions, the microphones were spaced a small distance apart in the streamwise direction and correlations were obtained. The turbulent surface pressure spectra upstream of detachment and downstream of the beginning of separation are discussed as well as measurements of turbulent velocity spectra and wavespeeds.

Simpson, R. L.↗

Large Eddy Simulation of a Film Cooling Flow Injected from an Inclined Discrete Cylindrical Hole into a Crossflow with Zero-Pressure Gradient Turbulent Boundary Layer

A Large Eddy Simulation (LES) is performed of a high blowing ratio (M = 1.7) film cooling flow with density ratio of unity. Mean results are compared with experimental data to show the degree of fidelity achieved in the simulation. While the trends in the LES prediction are a noticeable improvement over Reynolds-Averaged Navier-Stokes (RANS) predictions, there is still a lack a spreading on the underside of the lifted jet. This is likely due to the inability of the LES to capture the full range of influential eddies on the underside of the jet due to their smaller structure. The unsteady structures in the turbulent coolant jet are also explored and related to turbulent mixing characteristics

Johnson, Perry L.↗

Simulation and Modeling of Hypersonic Turbulent Boundary Layers Subject to Favorable Pressure Gradients due to Streamline Curvature

Direct numerical simulations (DNS) of favorable-pressure-gradient turbulent boundary layers are presented for a nominal freestream Mach number of 5, with the objective of assessing the limitations of the currently available Reynolds-averaged Navier-Stokes (RANS) models.The wall geometry and flow conditions of the DNS are representative of the experimental data for a Mach 4.9 turbulent boundary layer that was tested on a two-dimensional planar convexwall model in the high-speed blow-down wind tunnel located at the National Aerothermochemistry Laboratory at Texas A&M University. The favorable pressure gradient is induced bythe streamwise surface curvature. The DNS results will be compared with experimental measurements and RANS computations for the same flow conditions and wall geometry. The DNS datasets will also be analyzed to provide an improved physical understanding of hypersonic boundary-layer turbulence subject to mechanical nonequilibrium, including the validity of Morkovin’s hypothesis and the various available compressibility transformations, as well as to obtain turbulence statistics that are relevant to RANS modeling, including the distribution ofeddy viscosity, the budgets of turbulent kinetic energy and Reynolds stresses, and the velocity-temperature correlations. The RANS predictions will be obtained by using both the commonly used one- and two-equation models that assume a constant turbulent Prandtl number and an algebraic, variable Prandtl number model for the turbulent energy flux.

turbulent boundary layers↗

Experimental and numerical study of a turbulent boundary layer with pressure gradients

Results are presented of an experimental and numerical study of a turbulent boundary layer with pressure gradients conducted using the recent 'fringe method' with its numerical advantages and good inflow quality. After an inflow transient good agreement is observed; the differences, of up to 13 percent, are discussed. Moderate deviations from the law of the wall are found in the velocity profiles of the simulation. They are fully correlated with the pressure gradient, are in fair quantitative agreement with the experimental results of Nagano et al. (1992), and are roughly the opposite of uncorrected mixing-length-model predictions. Large deviations from the wall scaling are observed for other quantities, notably for the turbulence dissipation rate. The a(1) structure parameter drops mildly in the upper layer with adverse pressure gradient.

Spalart, Philippe R.↗

Simulation and Modeling of Hypersonic Turbulent Boundary Layers Subject to Adverse Pressure Gradients due to Concave Streamline Curvature

Direct numerical simulations (DNS) of adverse-pressure-gradient turbulent boundary layers over a planar concave wall are presented for a nominal freestream Mach number of 5, with the objective of assessing the limitations of the currently available Reynolds-averaged Navier-Stokes (RANS) models. The wall geometry and flow conditions of the DNS are representative of the experimental data for a Mach 4.9 turbulent boundary layer that was tested on a two-dimensional planar concave wall model in the high-speed blow-down wind tunnel located at the National Aerothermochemistry Laboratory at Texas A&M University (TAMU). The DNS was validated against the experimental results of TAMU for the same flow conditions and wall geometry. An analysis of the DNS datasets was also conducted to provide an assessment of the validity of Morkovin’s hypothesis and the strong Reynolds analog for turbulence subject to mechanical nonequilibrium. In addition to the DNS results, RANS predictions are obtained by using the Baldwin-Lomax (BL), Spalart-Allmaras (SA), and the k - w SST turbulence models. The comparisons between RANS and DNS showed little impact of an adverse pressure gradient on the accuracy of these models, at least up to an incompressible Clauser pressure gradient parameter of beta(sub inc) 1.22. While the Boussinesq assumption provided reasonable predictions for the Reynolds shear stress, it failed to adequately predict the normal components of the Reynolds stress.

turbulent boundary layers↗

Some features of surface pressure fluctuations in turbulent boundary layers with zero and favorable pressure gradients

Measurements of surface pressure fluctuation spectra, coherence and convective wave speeds from zero and favorable pressure gradient turbulent boundary layers are reported for momentum Reynolds numbers from 3000 to 18,800. The acceleration parameter K is near 2 x 10 to the -7 power for the favorable pressure gradient flow. The outer variables, U sub e, tau sub w and delta sub 1 non-dimensionalize and collapse the spectra for the low to middle range of frequencies for most test cases. The grouping using the inner variable, U sub tau and gamma, collapse the spectra for the middle to high range of frequencies for all test cases. The value of p'/tau sub w was near 3.8 and 2.8 for the smallest values of d+ in the zero and favorable pressure gradient flows, respectively. The coherence exhibits a decay that is not exponential in some cases, but the Corcos similarity parameters omega Delta x/U sub c and omega Delta z/U sub c collapse the data for all test cases. The ratio of U sub c/U sub e increases with omega delta sub 1/U sub e up to omega delta sub 1/U sub e on the order of unity, where U sub c/U sub e becomes nearly constant. This was observed in the present results for both streamwise pressure gradient flows. The experimental results presented show good agreement with previous research.

Mcgrath, B. E.↗

An experimental investigation of a swirling, axisymmetric, turbulent boundary layer with pressure gradient

The results of an experimental investigation designed to document data on both mean and turbulence quantities in the axisymmetric, swirling boundary layer (with and without a pressure gradient) flowing over a stationary cylinder downstream of a spinning cylindrical section are discussed. The pressure gradient was introduced into the flow field by a 25.4-mm-high, forward-facing circular step mounted on the stationary cylinder, the step height being nearly equal to the approaching boundary-layer thickness. All the measurements were made at upstream reference velocity of 36-37 m/sec, with the rotation of the spinner set to make its peripheral speed equal to the reference velocity. The data reported include measurements of surface pressure and the mean surface-shear-stress vector (using a miniature directional surface-fence gage) and oil-flow visualization studies of the stationary cylinder. The data indicate that the streamwise pressure gradient controls the development of the streamwise component of wall shear but leaves the peripheral component of wall shear practically unaffected.

Hebbar, S. K.↗

Direct Numerical Simulation of Smooth-Body Flow Separation Around a Ramp

Spanwise-periodic computation of a turbulent flow past a two-dimensional smooth ramp geometry is performed in the form of a direct numerical simulation. The Reynolds number based on the ramp height is about 147,000. A straight section that precedes the smooth ramp allows the incoming turbulent boundary layer to grow under a weak favorable pressure gradient. The boundary layer introduced at the domain inlet has a momentum-thickness based Reynolds number of 2000. The turbulent boundary layer nearing the ramp first interacts with a relatively stronger favorable pressure gradient, followed by a strong adverse pressure gradient. Consequently, the boundary layer experiences a modest acceleration before decelerating and separating. Analysis of the data over this region hints at the formation of an internal layer beneath the accelerated boundary layer. The analysis also reveals that this internal layer forms the origin of the free shear layer that emerges in the deceleration region and separates. The streamwise extent of the separated region is comparable to the ramp length, while the viscous layer thickness near reattachment is about the same as the ramp height; hence, the boundary layer undergoing separation and subsequent reattachment in the present configuration experiences its thickness being amplified by about tenfold. The reattached flow continues to develop further under a diminishing pressure gradient in the recovery region in a similar fashion to a zero pressure gradient turbulent boundary layer.

Turbulence↗

Turbulence measurements in the boundary layer of a low-speed wind tunnel using laser velocimetry

Laser velocimeter measurements in an incompressible, turbulent boundary layer along the wall of a low-speed wind tunnel are presented. The laser data are compared with existing hot-wire anemometer measurements of a flat plate, incompressible, turbulent, boundary layer with zero pressure gradient. An argument is presented to explain why previous laser velocimeter measurements in zero pressure gradient, turbulent boundary layers have shown an unexpected decrease in turbulent shear stresses near the wall.

Schairer, E. T.↗

A Galilean and tensorial invariant k-epsilon model for near wall turbulence

A k-epsilon model is proposed for wall bounded turbulent flows. In this model, the eddy viscosity is characterized by a turbulent velocity scale and a turbulent time scale. The time scale is bounded from below by the Kolmogorov time scale. The dissipation rate equation is reformulated using this time scale and no singularity exists at the wall. A new parameter R = k/S(nu) is introduced to characterize the damping function in the eddy viscosity. This parameter is determined by local properties of both the mean and the turbulent flow fields and is free from any geometry parameter. The proposed model is then Galilean and tensorial invariant. The model constants used are the same as in the high Reynolds number Standard k-epsilon Model. Thus, the proposed model will also be suitable for flows far from the wall. Turbulent channel flows and turbulent boundary layer flows with and without pressure gradients are calculated. Comparisons with the data from direct numerical simulations and experiments show that the model predictions are excellent for turbulent channel flows and turbulent boundary layers with favorable pressure gradients, good for turbulent boundary layers with zero pressure gradients, and fair for turbulent boundary layer with adverse pressure gradients.

Yang, Z.↗

Application of a general boundary layer analysis to turbulent boundary layers subjected to strong favorable pressure gradients

Theoretical predictions of turbulent boundary layer development under the influence of strong favorable pressure gradients made using a finite-difference calculation procedure are compared to experimental data. Comparisons are presented for low speed flows with and without wall heat transfer as well as for supersonic flows with adiabatic walls. The turbulence model used is governed by an integral form of the turbulence kinetic energy equation and the results are compared with predictions made using a conventional equilibrium turbulence model based upon Prandtl's mixing length, a Clauser-type eddy viscosity model used by Cebecci and Mosinskis, and a two-equation turbulence energy model of Launder and Jones.

Kreskovsky, J. P.↗