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All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Measurements of the Aeroacoustic Sound Source in Hot Jets

We have succeeded in measuring a substantial portion of the two-point space-time velocity correlation in hot, high speed turbulent jets. This measurement, crucial in aeroacoustic theory and the prediction of jet noise, has been sought for a long time, but has not been made due to the limitations of anemometry. Particle Image Velocimetry has reached a stage of maturity where sufficient measurement density in both time and space allow the computation of space-time correlations. This paper documents these measurements along with lower-order statistics to document the adherence of the jet rig and instrumentation to conventional measures of the turbulence of jets. These measures have been made for a simple round convergent nozzle at acoustic Mach numbers of 0.5, 0.9, both cold and at a static temperature ratio of 2.7, allowing some estimation of the changes in turbulence that take place with changes in jet temperature. Since the dataset described in this paper is very extensive, attention will be focused on validation of the rig and of the measurement systems, and on some of the interesting observations made from studying the statistics, especially as they relate to jet noise. Of note is the effort to study the acoustically relevant part of the space-time correlation by addressing that part of the turbulence kinetic energy that has sonic phase speed.

Bridges, James↗
NASA NTRS2018

Wall-Resolved Large-Eddy Simulations of Transonic Shock-Induced Flow Separation

Wall-resolved large-eddy simulations of shock-induced flow separation over an axisymmet- ric bump for a Mach number of 0.875 and a chord-based Reynolds number of 2.763 million are performed. The incoming boundary layer has a momentum-thickness Reynolds number of 6600 at 1.5 chords upstream of the bump. The calculations, which employ up to 24 billion grid points, simulate the experimental model of Bachalo and Johnson (AIAA Journal, Vol. 24, No. 3, 1986), except that the tunnel walls are ignored and free air is assumed. The effects of domain span and grid resolution are examined along with the main flowfield features. The predicted shock position as well as separation and reattachment locations agree well with the experiment. Grid convergence is observed in the attached region well upstream of separation. Two-point azimuthal correlations suggest that a span of at least 20 degrees is needed in the attached region, while a 120-degree span might be barely large enough in the separated region. Computed root-mean-square surface pressure fluctuations at the shock foot reach about 5 percent of ambient pressure and the level at reattachment location drops to about half of the primary peak. Simulations reveal evidence of the low-frequency shock unsteadiness; however, a much longer statistical sample is needed to investigate this phenomenon.

Uzun, Ali↗
NASA NTRS1994

Statistics and topology of the COBE differential microwave radiometer first-year sky maps

We use statistical and topological quantities to test the Cosmic Background Explorer (COBE) Differential Microwave Radiometer (DMR) first-year sky maps against the hypothesis that the observed temperature fluctuations reflect Gaussian initial density perturbations with random phases. Recent papers discuss specific quantities as discriminators between Gaussian and non-Gaussian behavior, but the treatment of instrumental noise on the data is largely ignored. The presence of noise in the data biases many statistical quantities in a manner dependent on both the noise properties and the unknown cosmic microwave background temperature field. Appropriate weighting schemes can minimize this effect, but it cannot be completely eliminated. Analytic expressions are presented for these biases, and Monte Carlo simulations are used to assess the best strategy for determining cosmologically interesting information from noisy data. The genus is a robust discriminator that can be used to estimate the power-law quadrupole-normalized amplitude, Q(sub rms-PS), independently of the two-point correlation function. The genus of the DMR data is consistent with Gaussian initial fluctuations with Q(sub rms-PS) = (15.7 +/- 2.2) - (6.6 +/- 0.3)(n - 1) micro-K, where n is the power-law index. Fitting the rms temperature variations at various smoothing angles gives Q(sub rms-PS) = 13.2 +/- 2.5 micro-K and n = 1.7(sup (+0.3) sub (-0.6)). While consistent with Gaussian fluctuations, the first year data are only sufficient to rule out strongly non-Gaussian distributions of fluctuations.

Smoot, G. F.↗
NASA NTRS1993

The velocity dispersion of the caustic network due to random motion of individual stars in the lensing galaxy

We present a method of computing the velocity distribution of the caustic network due to the random motion of stars in the lensing galaxy. This method is illustrated on the example of the two-point mass lens and then applied to a large sample of stars. We conclude that the proper motion of the stars increases significantly the frequency of the high magnification events in comparison with a static lens configuration with constant stream or constant bulk velocity. The stream velocity is the velocity of the star field relative to the global bulk velocity of the galaxy. We show that the global bulk and the stream velocity of the star field have to be considered separately for any microlensing situation. The higher the surface mass density of the stars in the lensing galaxy, the higher the influence of proper motion of stars on the statistics of high magnification events. The influence of a Gaussian velocity distribution of the stars in the lensing galaxy compared with a constant stream velocity of the stars increases the number of high magnification events by a factor 1.30 +/- 0.06 for a normalized surface density of the stars cr = 0.1 and by a factor 1.7 +/- 0.1 for sigma = 0.5. This means that for some microlensing situations the proper motion of the stars in a lensing galaxy has to be considered for exact microlensing predictions.

Kundik, Tomislav↗
NASA NTRS1991

Proper orthogonal decomposition based turbulence modeling

The proper orthogonal decomposition is utilized to provide one mode estimates of various turbulence quantities in the near-wall region of the turbulent boundary layer. The experimental data of Herzog (1986) and the direct numerical simulation (DNS) results of Zang (1991) proved the two-point correlation tensor. The correlation tensor is then used as the kernel in the integral eigenvalue problem from which the proper orthogonal modes are obtained. The one mode estimates of the turbulent kinetic energy, dissipation, and triple moments all exhibit the proper asymtotic behavior near the wall. As a validation test, a model for the triple moments is developed and its near-wall behavior is studied. This information can then be used to obtain an estimate of the damping function near the wall, which is then compared to known existing behavior. Since this is an initial investigation, the streamwise and spanwise dependence is surpressed and only the wall normal direction (y+) behavior of various turbulence statistics near the wall is studied. Before examining one mode estimates of the triple moments and the dissipation (on which the model is based), various second order moments are examined. If these do not exhibit the proper behavior near the wall (as discussed by Speziale et al 1990) it does not seem reasonable to expect the one mode estimate of the triple moment and dissipation to have the right behavior. Only the results obtained using the experimental data of Herzog are discussed since the results from the simulations of Zang exhibit similar behavior as discussed above.

Glauser, Mark N.↗
NASA NTRS1979

A statistical model of turbulence in two-dimensional mixing layers

A statistical model of turbulence in fully developed two-dimensional incompressible turbulent mixing layers is proposed. The development of this model is largely motivated by the recent experimental observations of Brown and Roshko (1974). The model is based on the proposition that the turbulence of a fully developed two-dimensional incompressible mixing layer is in a state of quasi-equilibrium. The model is used to predict the second-order turbulence statistics of the flow including single-point turbulent Reynolds stress distribution, intensity of turbulent velocity components, rms turbulent pressure fluctuations, power spectra and two-point space-time correlation functions. It is shown that numerical results compare favorably with available experimental measurements.

Tam, C. K. W.↗
NASA NTRS1982

Statistical analysis of piloted simulation of real time trajectory optimization algorithms

A simulation of time-optimal intercept algorithms for on-board computation of control commands is described. The effects of three different display modes and two different computation modes on the pilots' ability to intercept a moving target in minimum time were tested. Both computation modes employed singular perturbation theory to help simplify the two-point boundary value problem associated with trajectory optimization. Target intercept time was affected by both the display and computation modes chosen, but the display mode chosen was the only significant influence on the miss distance.

Price, D. B.↗
NASA NTRS1990

Stochastic estimation of coherent structures in turbulent boundary layers

The stochastic estimation technique is described as well as its extension to two-point and space-time conditional estimates. Based on the experimental data of Guezennec (1985), a comparison is made between the stochastic estimates and the conventional ensemble averaging results. As only the normal velocity and streamwise components were measured at each point on the sampling grid, the assumption of statistical symmetry in the spanwise direction about the centerline was used and the spanwise velocity component was reconstructed by integrating the continuity equation from the centerline outward.

Guezennec, Y. G.↗
NASA NTRS1994

Microwave background fluctuations due to the Sunyaev-Zel'dovich effects in pancakes

We calculate distortions in the microwave background radiation from the Sunyaev-Zel'dovich effect, produced by hot gas in large (approximately 100 Mpc) pancakes. The large-scale distribution of the pancakes is taken to be that of a Voronoi foam. Fluctuations for this scenario are estimated to be on the order of delta T/T is approximately 10(exp -5). Using computer simulations, we produce several 32 deg x 32 deg images with 0.25 deg resolution. These images show characteristic linear features produced when a pancake is viewed nearly edge-on. By calculating the two-point and the degenerate three-point correlation functions, we are able to statistically detect such non-Gaussian features even in the presence of a relatively large amount of Gaussian noise. The degenerate three-point correlation function is found to be particularly useful since it is insensitive to correlated Gaussian noise. We also smooth our data over a 7 deg Full Width at Half Maximum (FWHM) Gaussian window to simulate the Cosmic Background Explorer Satellite (COBE) observations. We find that under such low-resolution conditions, the features are highly suppressed.

Subbarao, M. U.↗
NASA NTRS1995

Gaussian statistics of the cosmic microwave background: Correlation of temperature extrema in the COBE DMR two-year sky maps

We use the two-point correlation function of the extrema points (peaks and valleys) in the Cosmic Background Explorer (COBE) Differential Microwave Radiometers (DMR) 2 year sky maps as a test for non-Gaussian temperature distribution in the cosmic microwave background anisotropy. A maximum-likelihood analysis compares the DMR data to n = 1 toy models whose random-phase spherical harmonic components a(sub lm) are drawn from either Gaussian, chi-square, or log-normal parent populations. The likelihood of the 53 GHz (A+B)/2 data is greatest for the exact Gaussian model. There is less than 10% chance that the non-Gaussian models tested describe the DMR data, limited primarily by type II errors in the statistical inference. The extrema correlation function is a stronger test for this class of non-Gaussian models than topological statistics such as the genus.

Kogut, A.↗
NASA NTRS1995

Diagnostic Statistics for the Assessment and Characterization of Complex Turbulent Flows

A simple parameterization scheme for a complex turbulent flow using nondimensional parameters coming from the Reynolds stress equations is given. Definitions and brief descriptions of the physical significance of several nondimensional parameters that are used to characterize turbulence from the viewpoint of single-point turbulence closures are given. These nondimensional parameters reflect measures of (1) the spectral band width of the turbulence; (2) deviations from the ideal Kolmogorov behavior; (3) the relative magnitude, orientation, and temporal duration of the deformation to which the turbulence is subjected; (4) one and two-point measures of the large and small scale anisotropy of the turbulence; and (5) inhomogeneity. This is an attempt to create a more systematic methodology for the diagnosis and classification of turbulent flows as well as in the development, validation, and application of turbulence model strategies. The parameters serve also to indicate the adequacy of various assumptions made in single-point turbulence models and in suggesting the appropriate turbulence strategy for a particular complex flow. The compilation will be of interest to experimentalists and to those involved in either computing turbulent flows or whose interests lies in verifying the adequacy of the phenomenological beliefs used in turbulence closures.

Ristorcelli, J. R.↗
NASA NTRS1999

Ocean Turbulence: Two-Point Closure Model Momentum, Heat and Salt Vertical Diffusivities in the Presence of Shear - Paper 3

In papers 1 and 2 we have presented the results of the most updated 1-point closure model for the turbulent vertical diffusivities of momentum, heat and salt, K(sub m,h,s). In this paper, we derive the analytic expressions for K(sub m,h,s) using a new 2-point closure model that has recently been developed and successfully tested against some approx. 80 turbulence statistics for different flows. The new model has no free parameters. The expressions for K(sub m, h. s) are analytical functions of two stability parameters: the Turner number R(sub rho) (salinity gradient/temperature gradient) and the Richardson number R(sub i) (temperature gradient/shear). The turbulent kinetic energy K and its rate of dissipation may be taken local or non-local (K-epsilon model). Contrary to all previous models that to describe turbulent mixing below the mixed layer (ML) have adopted three adjustable "background diffusivities" for momentum. heat and salt, we propose a model that avoids such adjustable diffusivities. We assume that below the ML, K(sub m,h,s) have the same functional dependence on R(sub i) and R(sub rho) derived from the turbulence model. However, in order to compute R(sub i) below the ML, we use data of vertical shear due to wave-breaking measured by Gargett et al. (1981). The procedure frees the model from adjustable background diffusivities and indeed we use the same model throughout the entire vertical extent of the ocean. Using the new K(sub m,h, s), we run an O-GCM and present a variety of results that we compare with Levitus and the KPP model. Since the traditional 1-point (used in papers 1 and 2) and the new 2-point closure models used here represent different modeling philosophies and procedures, testing them in an O-GCM is indispensable. The basic motivation is to show that the new 2-point closure model gives results that are overall superior to the 1-point closure in spite of the fact that the latter rely on several adjustable parameters while the new 2-point closure has none. After the extensive comparisons presented in papers 1 and 2, we conclude that the new model presented here is overall superior for it not only is parameter free but also 2 because is part of a more general turbulence model that has been previously successfully tested on a wide variety of other types of turbulent flows.

Canuto, V. M.↗