Evolution and convection of large-scale structures in supersonic reattaching shear flows

1999 ◽  
Vol 11 (8) ◽  
pp. 2127-2138 ◽  
Author(s):  
K. M. Smith ◽  
J. C. Dutton
Keyword(s):  
Large Scale ◽  
Shear Flows ◽  
Large Scale Structures ◽  
Scale Structures

Large scale structures in free turbulent shear flows

1997 ◽  
Author(s):  
J. Bonnet ◽  
J. Delville ◽  
M. Glauser ◽  
J. Bonnet ◽  
J. Delville ◽  
...  
Keyword(s):  
Large Scale ◽  
Shear Flows ◽  
Turbulent Shear ◽  
Large Scale Structures ◽  
Turbulent Shear Flows ◽  
Scale Structures

On the turbulent mixing of compressible free shear layers

1990 ◽  
Vol 431 (1882) ◽  
pp. 219-243 ◽  
Keyword(s):  
Stability Analysis ◽  
Shear Layer ◽  
Turbulent Mixing ◽  
Large Scale ◽  
Shear Flows ◽  
Time Dependent ◽  
Turbulent Shear ◽  
Large Scale Structures ◽  
Turbulent Shear Flows ◽  
Scale Structures

For over a quarter of a century it has been recognized that turbulent shear flows are dominated by large-scale structures. Yet the majority of models for turbulent mixing fail to include the properties of the structures either explicitly or implicitly. The results obtained using these models may appear to be satisfactory, when compared with experimental observations, but in general these models require the inclusion of empirical constants, which render the predictions only as good as the empirical database used in the determination of such constants. Existing models of turbulence also fail to provide, apart from its stochastic properties, a description of the time-dependent properties of a turbulent shear flow and its development. In this paper we introduce a model for the large-scale structures in a turbulent shear layer. Although, with certain reservations, the model is applicable to most turbulent shear flows, we restrict ourselves here to the consideration of turbulent mixing in a two-stream compressible shear layer. Two models are developed for this case that describe the influence of the large-scale motions on the turbulent mixing process. The first model simulates the average behaviour by calculating the development of the part of the turbulence spectrum related to the large-scale structures in the flow. The second model simulates the passage of a single train of large-scale structures, thereby modelling a significant part of the time-dependent features of the turbulent flow. In both these treatments the large-scale structures are described by a superposition of instability waves. The local properties of these waves are determined from linear, inviscid, stability analysis. The streamwise development of the mean flow, which includes the amplitude distribution of these instability waves, is determined from an energy integral analysis. The models contain no empirical constants. Predictions are made for the effects of freestream velocity and density ratio as well as freestream Mach number on the growth of the mixing layer. The predictions agree very well with experimental observations. Calculations are also made for the time-dependent motion of the turbulent shear layer in the form of streaklines that agree qualitatively with observation. For some other turbulent shear flows the dominant structure of the large eddies can be obtained similarly using linear stability analysis and a partial justification for this procedure is given in the Appendix. In wall-bounded flows a preliminary analysis indicates that a linear, viscous, stability analysis must be extended to second order to derive the most unstable waves and their subsequent development. The extension of the present model to such cases and the inclusion of the effects of chemical reactions in the models are also discussed.

Some comments about observations and image processing of comet 29P/Schwassmann-Wachmann 1

1999 ◽  
Vol 173 ◽  
pp. 243-248
Author(s):  
D. Kubáček ◽  
A. Galád ◽  
A. Pravda
Keyword(s):  
Image Processing ◽  
Large Scale ◽  
Harvard College ◽  
Oak Ridge ◽  
Large Scale Structures ◽  
Short Period Comet ◽  
Short Period ◽  
Scale Structures ◽  
Harvard College Observatory ◽  
Period Comet

AbstractUnusual short-period comet 29P/Schwassmann-Wachmann 1 inspired many observers to explain its unpredictable outbursts. In this paper large scale structures and features from the inner part of the coma in time periods around outbursts are studied. CCD images were taken at Whipple Observatory, Mt. Hopkins, in 1989 and at Astronomical Observatory, Modra, from 1995 to 1998. Photographic plates of the comet were taken at Harvard College Observatory, Oak Ridge, from 1974 to 1982. The latter were digitized at first to apply the same techniques of image processing for optimizing the visibility of features in the coma during outbursts. Outbursts and coma structures show various shapes.

scholarly journals The organization and control of an evolving interdependent population

2015 ◽  
Vol 12 (108) ◽  
pp. 20150044 ◽  
Author(s):  
Dervis C. Vural ◽  
Alexander Isakov ◽  
L. Mahadevan
Keyword(s):  
Evolutionary Game Theory ◽  
Large Scale ◽  
Social Evolution ◽  
Evolutionary Game ◽  
Large Scale Structures ◽  
External Perturbations ◽  
Emergence Of Cooperation ◽  
Scale Structures ◽  
And Control ◽  
Evolutionarily Stable

Starting with Darwin, biologists have asked how populations evolve from a low fitness state that is evolutionarily stable to a high fitness state that is not. Specifically of interest is the emergence of cooperation and multicellularity where the fitness of individuals often appears in conflict with that of the population. Theories of social evolution and evolutionary game theory have produced a number of fruitful results employing two-state two-body frameworks. In this study, we depart from this tradition and instead consider a multi-player, multi-state evolutionary game, in which the fitness of an agent is determined by its relationship to an arbitrary number of other agents. We show that populations organize themselves in one of four distinct phases of interdependence depending on one parameter, selection strength. Some of these phases involve the formation of specialized large-scale structures. We then describe how the evolution of independence can be manipulated through various external perturbations.

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