Space Shuttle response to atmospheric turbulence

1973 ◽  
Author(s):  
R. HUNTINGTON
Keyword(s):  
Atmospheric Turbulence ◽  
Space Shuttle ◽  
Shuttle Response

Space Shuttle response to ascent wind profiles

1983 ◽  
Vol 6 (5) ◽  
pp. 355-360 ◽  
Author(s):  
Orvel E. Smith ◽  
Lambert D. Austin
Keyword(s):  
Space Shuttle ◽  
Wind Profiles ◽  
Shuttle Response

The effect of back-melting on the continuity of crystallographic orientation and composition in HgZnTe

1992 ◽  
Vol 50 (2) ◽  
pp. 1696-1697
Author(s):  
H.J. Zuo ◽  
M.W. Price ◽  
R.D. Griffin ◽  
R.A. Andrews ◽  
G.M. Janowski
Keyword(s):  
Directional Solidification ◽  
Space Shuttle ◽  
Solidification Process ◽  
Space Experiment ◽  
Infrared Detection ◽  
Directionally Solidified ◽  
Crystallographic Defects ◽  
Semiconducting Alloys ◽  
Uniform Composition ◽  
Growth Experiments

The II-VI semiconducting alloys, such as mercury zinc telluride (MZT), have become the materials of choice for numerous infrared detection applications. However, compositional inhomogeneities and crystallographic imperfections adversly affect the performance of MZT infrared detectors. One source of imperfections in MZT is gravity-induced convection during directional solidification. Crystal growth experiments conducted in space should minimize gravity-induced convection and thereby the density of related crystallographic defects. The limited amount of time available during Space Shuttle experiments and the need for a sample of uniform composition requires the elimination of the initial composition transient which occurs in directionally solidified alloys. One method of eluding this initial transient involves directionally solidifying a portion of the sample and then quenching the remainder prior to the space experiment. During the space experiment, the MZT sample is back-melted to exactly the point at which directional solidification was stopped on earth. The directional solidification process then continues.

Upgrades to the caution and warning system of the space shuttle

2003 ◽  
Author(s):  
Jeffrey W. McCandless ◽  
Robert S. McCann ◽  
Bruce R. Hilty
Keyword(s):  
Space Shuttle ◽  
Warning System

Prediction of Atmospheric Turbulence Characteristics for Surface Boundary Layer using Empirical Spectral Methods

2020 ◽  
Author(s):  
Yagya Dutta Dwivedi ◽  
Vasishta Bhargava Nukala ◽  
Satya Prasad Maddula ◽  
Kiran Nair
Keyword(s):  
Boundary Layer ◽  
Time Series ◽  
Surface Roughness ◽  
Wind Speed ◽  
Atmospheric Turbulence ◽  
Surface Boundary ◽  
Low Frequencies ◽  
Surface Boundary Layer ◽  
Power Spectral ◽  
Mean Wind Speed

Abstract Atmospheric turbulence is an unsteady phenomenon found in nature and plays significance role in predicting natural events and life prediction of structures. In this work, turbulence in surface boundary layer has been studied through empirical methods. Computer simulation of Von Karman, Kaimal methods were evaluated for different surface roughness and for low (1%), medium (10%) and high (50%) turbulence intensities. Instantaneous values of one minute time series for longitudinal turbulent wind at mean wind speed of 12 m/s using both spectra showed strong correlation in validation trends. Influence of integral length scales on turbulence kinetic energy production at different heights is illustrated. Time series for mean wind speed of 12 m/s with surface roughness value of 0.05 m have shown that variance for longitudinal, lateral and vertical velocity components were different and found to be anisotropic. Wind speed power spectral density from Davenport and Simiu profiles have also been calculated at surface roughness of 0.05 m and compared with k−1 and k−3 slopes for Kolmogorov k−5/3 law in inertial sub-range and k−7 in viscous dissipation range. At high frequencies, logarithmic slope of Kolmogorov −5/3rd law agreed well with Davenport, Harris, Simiu and Solari spectra than at low frequencies.

Estimating Atmospheric Turbulence Parameters from the Envelopes of Radio Acoustic Signals

2001 ◽  
Vol 55 (8) ◽  
pp. 5
Author(s):  
V. M. Kartashov ◽  
V. A. Petrov ◽  
Ye. G. Proshkin ◽  
G. I. Sidorov
Keyword(s):  
Atmospheric Turbulence ◽  
Acoustic Signals ◽  
Turbulence Parameters
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