Surface Fluctuation Analysis for Turbulent Liquid Sheets

2004 ◽  
Vol 45 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Samuel G. Durbin ◽  
Timothy P. Koehler ◽  
Jefferey J. R. Reperant ◽  
Minami Yoda ◽  
Said I. Abdel-Khalik ◽  
...  
Keyword(s):  
Fluctuation Analysis ◽  
Liquid Sheets ◽  
Surface Fluctuation

The Experimental Research of Stabilize Water Delivery on Varying Water Head and Non Pressure Water Tunnel

2013 ◽  
Vol 353-356 ◽  
pp. 2468-2472
Author(s):  
Bo Yang
Keyword(s):  
Steady Flow ◽  
Water Surface ◽  
Comparative Trial ◽  
Free Flow ◽  
Fluctuation Analysis ◽  
Water Delivery ◽  
Water Project ◽  
Water Head ◽  
Pressure Water ◽  
Surface Fluctuation

The simple and efficient facilities of steady flow and wave elimination-flow-stabilizing plate and wave-eliminating barrier were introduced to study strong water surface fluctuation existing in free flow tunnel in Aan water project, through comparative trial and fluctuation analysis, it could be found that the introduction of steady-flow and wave-elimination facilities could stabilize the flow pattern of free flow tunnel.

ON THE STABILITY OF LIQUID SHEETS IN HOT ATMOSPHERES

1998 ◽  
Vol 8 (2) ◽  
pp. 235-240 ◽  
Author(s):  
E. A. Foumeny ◽  
N. Dombrowski
Keyword(s):  
Liquid Sheets ◽  
The Stability

CAPILLARY STABILITY OF MODULATED SWIRLING LIQUID SHEETS;

2004 ◽  
Vol 14 (5) ◽  
pp. 397-436 ◽  
Author(s):  
C. Mehring ◽  
William A. Sirignano
Keyword(s):  
Liquid Sheets ◽  
Capillary Stability

Fluctuation Analysis of Liquid/Liquid and Gel/Liquid Interfaces

1989 ◽  
Author(s):  
Vladimir Marecek ◽  
Miklos Gratzl ◽  
Angras Pungor ◽  
Jiri Janata
Keyword(s):  
Fluctuation Analysis ◽  
Liquid Interfaces

SCALING ANALYSIS OF THE A-PHASE DYNAMICS DURING SLEEP

Fractals ◽  
2020 ◽  
Vol 28 (02) ◽  
pp. 2050050
Author(s):  
V. E. ARCE-GUEVARA ◽  
M. O. MENDEZ ◽  
J. S. MURGUÍA ◽  
A. ALBA ◽  
H. GONZÁLEZ-AGUILAR ◽  
...  
Keyword(s):  
Binary Sequence ◽  
Fluctuation Analysis ◽  
Scaling Analysis ◽  
Scaling Exponent ◽  
Sleep State ◽  
Phase Dynamics ◽  
A Value ◽  
Sleep Condition ◽  
Detrended Fluctuation

In this work, the scaling behavior of the sleep process is evaluated by using detrended fluctuation analysis based on wavelets. The analysis is carried out from arrivals of short and recurrent cortical events called A-phases, which in turn build up the Cyclic Alternating Pattern phenomenon, and are classified in three types: A1, A2 and A3. In this study, 61 sleep recordings corresponding to healthy, nocturnal frontal lobe epilepsy patients and sleep-state misperception subjects, were analyzed. From the A-phase annotations, the onsets were extracted and a binary sequence with one second resolution was generated. An item in the sequence has a value of one if an A-phase onset occurs in the corresponding window, and a value of zero otherwise. In addition, we consider other different temporal resolutions from 2[Formula: see text]s to 256[Formula: see text]s. Furthermore, the same analysis was carried out for sequences obtained from the different types of A-phases and their combinations. The results of the numerical analysis showed a relationship between the time resolutions and the scaling exponents; specifically, for higher time resolutions a white noise behavior is observed, whereas for lower time resolutions a behavior towards to [Formula: see text]-noise is exhibited. Statistical differences among groups were observed by applying various wavelet functions from the Daubechies family and choosing the appropriate sequence of A-phase onsets. This scaling analysis allows the characterization of the free-scale dynamic of the sleep process that is specific for each sleep condition. The scaling exponent could be useful as a diagnosis parameter in clinics when sleep macrostructure does not offer enough information.

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