Prediction Of Turbulent Boundary Layers Research Articles

Research on aero-optical prediction of supersonic turbulent boundary layer based on aero-optical linking equation.

With the development of airborne imaging devices on the high-speed vehicle, aero-optical prediction of the turbulent boundary layer has attracted wide publicity. Based on the density distribution of supersonic (Mach 3.0) turbulent boundary layer obtained by nano-tracer-based planar laser scattering (NPLS) technique, we find that the time distribution characteristics of density fluctuation deviate from the Gaussian distribution mainly induced by the intermittency of a turbulent boundary layer. It may cause the prediction error of Sutton's linking equation to increase. The deflection-angle amplitude spectrum has a peak value at Stδ ≈1. With the increase of Stδ, the deflection-angle amplitude spectrum is more attenuated, which means that small-scale vortices make a relatively weak contribution to aero-optics, and which is mainly induced by large-scale vortices. With the assumption of locally homogeneous turbulence, the integral scale Λ is basically around 0.1δ. Without the assumption of locally homogeneous turbulence, the integral scale Λ is basically around 0.05δ. For the supersonic turbulent boundary layer with obvious inhomogeneity, based on the turbulence integral scale defined without the assumption of locally homogeneous turbulence, a fine aero-optical prediction result could also be obtained via the Sutton's linking equation. From the covariance distribution of density fluctuation, the prediction result based on the exponential distribution approximation is worse than that based on the Gaussian distribution approximation. The prediction effect is also shown through the change in coefficient. The prediction deviation of OPDrms based on the exponential distribution approximation is larger than that based on the Gaussian distribution approximation.

Prediction of Turbulent Boundary Layers with Wall Melting and Solidification

Prediction of Turbulent Boundary Layers with Wall Melting and Solidification

Prediction of turbulent boundary layer induced noise in the cabin of a BWB aircraft

This paper discusses the development of analytical models for the prediction of aircraft cabin noise induced by the external turbulent boundary layer (TBL). While, in previous works, the contribution of an individual panel to the cabin interior noise was considered, here, the simultaneous contribution of multiple flow-excited panels is analyzed. Analytical predictions are presented for the interior sound pressure level (SPL) at different locations inside the cabin of a Blended Wing Body (BWB) aircraft, for the frequency range 0-1000 Hz. The results show that the number of vibrating panels significantly affects the interior noise levels. Itis shown that the average SPL,over the cabin volume, increases with the number of vibrating panels. Additionally, the model is able to predict local SPL values, at specific locations in the cabin, which are also affected with by number of vibrating panels, and are different from the average values.

Prediction of Turbulent Boundary Layer Induced Noise in the Cabin of a BWB Aircraft

This paper discusses the development of analytical models for the prediction of aircraft cabin noise induced by the external turbulent boundary layer (TBL). While, in previous works, the contribution of an individual panel to the cabin interior noise was considered, here, the simultaneous contribution of multiple flow-excited panels is analyzed. Analytical predictions are presented for the interior sound pressure level (SPL) at different locations inside the cabin of a Blended Wing Body (BWB) aircraft, for the frequency range 0–1000 Hz. The results show that the number of vibrating panels significantly affects the interior noise levels. It is shown that the average SPL, over the cabin volume, increases with the number of vibrating panels. Additionally, the model is able to predict local SPL values, at specific locations in the cabin, which are also affected with by number of vibrating panels, and are different from the average values.

Numerical prediction of turbulent boundary layer subjected to a sudden transverse strain at the wall

This study is about the behaviour of a two dimensional turbulent boundary layer on a flat plate subjected to a transverse motion of the bounding wall, producing a sudden shear force. The resulted flow is three-dimensional. Numerical prediction is achieved using the k-e model at high Reynolds number with the assumption of an isotropic turbulent viscosity. Close wall treatment constitutes the main difficulty within the three-dimensional turbulent boundary layer modelling. Therefore, we propose a law of wall along the transverse direction. Whilst the standard logarithmic function suggested in the literature for the two-dimensional case is used for the longitudinal component.

Prediction of Turbulent Boundary Layers With a Second-Moment Closure: Part I—Effects of Periodic Pressure Gradient, Wall Transpiration, and Free-Stream Turbulence

The purpose of this two-part paper is to assess the performance of a second-moment closure applicable up to a wall. In the present part, the turbulence model is applied to the boundary layers with periodic pressure gradient, with wall transpiration and with free-stream turbulence. The predictions are shown to be in good agreement with experiments and a direct simulation. In particular, a tendency towards relaminarization and a subsequent retransition in the oscillating boundary layer are faithfully reproduced, and the effect of the length scale of free-stream turbulence is correctly captured.

Prediction of Turbulent Boundary Layers With a Second-Moment Closure: Part II—Effects of Streamline Curvature and Spanwise Rotation

Further testing of the second-moment closure employed in Part I is made. The present part considers the effects of streamline curvature and spanwise system rotation. As expected, the exact stress production terms broadly account for these effects. In addition, the present model, which is applied right up to a wall, successfully captures the laminarization in the rotating boundary layer. Attention is also given to the capability to reproduce the recovery process from curvature.

A Mixing-Length Model for the Prediction of Convex Curvature Effects on Turbulent Boundary Layers

A mixing-length model is developed for the prediction of turbulent boundary layers with convex streamwise curvature. For large layer thickness ratio, δ/R > 0.05, the model scales mixing length on the wall radius of curvature, R. For small δ/R, ordinary flat wall modeling is used for the mixing-length profile with curvature corrections, following the recommendations of Eide and Johnston [7]. Effects of streamwise change of curvature are considered; a strong lag from equilibrium is required when R increases downstream. Fifteen separate data sets were compared, including both hydrodynamic and heat transfer results. In this paper, six of these computations are presented and compared to experiment.

Deceleration Rate Parameter and Algebraic Prediction of Turbulent Boundary Layer

The deceleration rate θ1/λ, which is defined as the ratio of the momentum thickness to the distance where the free-stream velocity is reduced by 10 percent, is shown as an important and handy parameter to describe the development of turbulent boundary layer in an adverse pressure gradient. Using this parameter a simple calculation procedure of turbulent boundary layer is presented. In order to achieve a large inlet/exit velocity ratio, θ1/λ =0.02 may be recommended, where the influence of wall friction on the development of momentum loss is very small and the shape factor of boundary layer does not increase rapidly.

Closure to “Discussion of ‘Deceleration Rate Parameter and Algebraic Prediction of Turbulent Boundary Layer’” (1977, ASME J. Fluids Eng., 99, p. 394)

Closure to “Discussion of ‘Deceleration Rate Parameter and Algebraic Prediction of Turbulent Boundary Layer’” (1977, ASME J. Fluids Eng., 99, p. 394)

Errata: Prediction of Turbulent Boundary Layers at Low Reynolds Numbers

Fig. 2 Vorticity of trailing vortex measured by vorticity meter. bulence, Rept. 74-01, Feb. 1974, Rochester Applied Science Associates, Rochester, N.Y. Poppleton, E.D., Preliminary Experimental of the of a Turbulent Trailing Vortex, TN 71-1, May 1971, McGill University, Montreal, Canada. Kantha, H.L., Lewellen, W.S., and Durgin, F.H., Qualitative Responses of a Core to Tip Blowing and Intersecting Airfoils, ASRL-TR 153-4, Aug. 1971, Massachusetts Institute of Technology, Cambridge, Mass. McCormick, B.W., Tangier, J.L., and Sherrieb, H.E., Structure of Trailing Vortices, Journal of Aircraft, Vol. 5, March 1968, p. 260. 5 White, R.P. and Balcerak, J.C., Investigation of the Dissipation of the Tip of a Rotor Blade by Mass Injection, TR 72-43, 1972, USAAMRDL, Ft. Eustis, Va., 1972. Sheath, D.D., Vortex Airfoil Interaction Tests, Proceedings of the AIAA 2nd Atmospheric Flight Mechanics Conference, Sept. 1972, Palo Alto, Calif. Corsiglia, V.R., Schwind, P.G., and Chigier, N.A., Rapid Scanning, Three-Dimensional, Hot-Wire Anemometer Surveys for Wing Tip Vortices in the Ames 40-by 80-Foot Wind Tunnel, AIAA Paper 73-629, Palm Springs, Calif., 1973. Orloff, K.L. and Grant, G.R., The Application of A Scanning Laser Doppler Velocimeter to Trailing Definition and Alleviation, AIAA Paper 73-680, Palm Springs, Calif., 1973. Marchman, J.F., III and Uzel, J.N., Effect of Several Wing Tip Modifications on a Trailing Vortex, Journal of Aircraft, Vol. 9, Sept. 1972, pp. 684-686.

Prediction of turbulent boundary layers on cones at incidence

Conclusions Advances in technique and several new applications have been enumerated. These advances are seen as part of a continuing program to develop an automated production-type holographic interferometry system capable of threedimensional quantitative flow-field measurement. Future work will be directed toward completion of the computerized reader scanner system described in Ref. 1.

Comment on "Prediction of Turbulent Boundary Layers at Low Reynolds Numbers"

tion equations. In one special case [B] is [A T ] , but the result is very poor for most practical truss problems. Thus, although the solution (3) satisfies the conditions (1), (2), (4), and (6), it does not necessarily give the best values for the Xj in applications. It can be used as a starting point for the solution and can be taken as a solution if nothing other than Eq. (1) is known about the system. Obviously, in applications it is desirable to have sufficient known conditions to solve the problem, or m = n.

Prediction of turbulent boundary layers at low Reynolds numbers

Prediction of turbulent boundary layers at low Reynolds numbers