scholarly journals Spatio-temporal development of the long and short-wave vortex-pair instabilities

2000 ◽  
Vol 12 (5) ◽  
pp. 1247-1250 ◽  
Author(s):  
David Fabre ◽  
Carlo Cossu ◽  
Laurent Jacquin
Keyword(s):  
Vortex Pair ◽  
Short Wave ◽  
Temporal Development ◽  
Spatio Temporal

scholarly journals Short-wave instabilities on a vortex pair of unequal strength circulation ratio

2011 ◽  
Vol 35 (4) ◽  
pp. 1581-1590 ◽  
Author(s):  
Joine So ◽  
Kris Ryan ◽  
Gregory J. Sheard
Keyword(s):  
Vortex Pair ◽  
Short Wave ◽  
Circulation Ratio ◽  
Wave Instabilities

Spatio-Temporal Development of Supercavitation Over an Impulsively Launched Projectile

2006 ◽  
Author(s):  
C. J. Weiland ◽  
P. P. Vlachos
Keyword(s):  
High Speed ◽  
Temporal Development ◽  
Two Phase ◽  
Time Resolved ◽  
Gas Gun ◽  
Supercavitating Flow ◽  
Image Velocimetry ◽  
Spatio Temporal ◽  
Asymmetric Vortices ◽  
First Time

Supercavitation inception and formation was studied over blunt projectiles. The projectiles were fired using a gas gun method. In this method, projectiles are launched under the action of expanding detonation gases. Both qualitative and quantitative optical flow diagnostics using high speed digital imaging were used to analyze the spatio-temporal development of the supercavitating flow. For the first time, quantification of the supercavitation was achieved using Time Resolved Digital Particle Image Velocimetry (TRDPIV) detailing the two phase flow field surrounding the translating projectiles and the gas vapor bubble. Experimental results indicate that the supercavity forms at the aft end of the projectile and travels forward along the direction of projectile travel. The impulsive start of the projectile generates two asymmetric vortices which are shed from the blunt nose of the projectile. The vortices interact with the moving cavity and subsequently deform. This interaction is believed to directly contribute to the instabilities in the flight path.

Flow/Acoustic Mechanisms in Three-Dimensional Vortices Undergoing Sinusoidal-Wave Instabilities

2007 ◽  
Author(s):  
Wenhua Li ◽  
Z. C. Zheng ◽  
Ying Xu
Keyword(s):  
Flow Field ◽  
Three Dimensional ◽  
Vortex Pair ◽  
Particle Method ◽  
Acoustic Signals ◽  
Short Wave ◽  
Vortical Flow ◽  
Vortex Particle Method ◽  
Structure Changes ◽  
Wave Instabilities

It has been identified that vorticity in a vortex core directly relates to the frequency of a significant sound peak from an aircraft wake vortex pair where each of the vortices is modeled as an elliptic core Kirchhoff vortex. In three-dimensional vortices, sinusoidal instabilities at various length scales result in significant flow structure changes in these vortices, and thus influence their radiated acoustic signals. In this study, a three-dimensional vortex particle method is used to simulate the incompressible vortical flow. The flow field, in the form of vorticity, is employed as the source in the far-field acoustic calculation using a vortex sound formula that enables computation of acoustic signals radiated from an approximated incompressible flow field. Cases of vortex rings and a pair of counter-rotating vortices are studied when they are undergoing both long- and short-wave instabilities. Both inviscid and viscous interactions are considered and effects of turbulence are simulated using sub-grid-scale models.

scholarly journals Reconstructing the Spatio-Temporal Development of Irrigation Systems in Uzbekistan Using Landsat Time Series

2012 ◽  
Vol 4 (12) ◽  
pp. 3972-3994 ◽  
Author(s):  
Jana Edlinger ◽  
Christopher Conrad ◽  
John Lamers ◽  
Gulchekhra Khasankhanova ◽  
Thomas Koellner
Keyword(s):  
Time Series ◽  
Temporal Development ◽  
Irrigation Systems ◽  
Spatio Temporal

62. Spatio-temporal development of structural and functional abnormalities of heparan sulfate in the brain of a mouse model of Hurler syndrome

2009 ◽  
Vol 96 (2) ◽  
pp. S25-S26
Author(s):  
Pankaj Gupta ◽  
Katherine Murphy ◽  
Matthew Nelson ◽  
Melissa Rusch ◽  
Zhenhong Nan ◽  
...  
Keyword(s):  
Mouse Model ◽  
Heparan Sulfate ◽  
Hurler Syndrome ◽  
Temporal Development ◽  
Spatio Temporal ◽  
The Brain

Revealing snow cover dynamics in the Hindu Kush Himalaya over the past decades

2020 ◽  
Author(s):  
Kathrin Naegeli ◽  
Carlo Marin ◽  
Valentina Premier ◽  
Gabriele Schwaizer ◽  
Martin Stengel ◽  
...  
Keyword(s):  
High Resolution ◽  
Snow Cover ◽  
Satellite Data ◽  
Weather Forecast ◽  
Short Wave ◽  
Climate Modelling ◽  
Snow Cover Area ◽  
Hindu Kush ◽  
Spatio Temporal ◽  
Area Percentage

<p>Knowledge about the snow cover distribution is of high importance for climate studies, weather forecast, hydrological investigations, irrigation or tourism, respectively. The Hindu Kush Himalayan (HKH) region covers almost 3.5 million km<sup>2</sup> and extends over eight different countries. The region is known as ‘water tower’ as it contains the largest volume of ice and snow outside of the polar ice sheets and it is the source of Asia’s largest rivers. These rivers provide ecosystem services, the basis for livelihoods and most importantly living water for drinking, irrigation, energy production and industry for two billion people, a fourth of the world’s population, living in the mountains and downstream.</p><p>The spatio-temporal variability of snow cover in the HKH is high and studies reported average snow-covered area percentage of 10–18%, with greater variability in winter (21–42%) than in summer (2–4%). However, no study systematically investigated snow cover metrics, such as snow cover area percentage (SCA), snow cover duration (SCD) or snow cover onset (SCOD) and melt-out day (SCMD), for the entire region so far. Here, we thus present unique in-sights of regional and sub-regional snow cover dynamics for the HKH based on almost four decades, an exceptionally long and in view of the climate modelling community valuable timeseries, of satellite data obtained within the ESA CCI+ Snow project.</p><p>Our results are based on Advanced Very High Resolution Radiometer (AVHRR) data, collected onboard the polar orbiting satellites NOAA-7 to -19, providing daily, global imagery at a spatial resolution of 5 km. Calibrated and geocoded reflectance data and a consistent cloud mask pre-processed and provided by the ESA Cloud_cci project as global 0.05° composites are used. The retrieval of snow extent considers the high reflectance of snow in the visible spectra and the low reflectance values in the short-wave infrared expressed in the Normalized Difference Snow Index (NDSI). Additional thresholds related to topography and land cover are included to derive the fractional snow cover of every pixel. A temporal gap-filling was applied to mitigate the influence of clouds. Reference snow maps from high-resolution optical satellite data as well as in-situ station data were used to validate the time series.</p>

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