A stochastic method to account for the ambient turbulence in Lagrangian Vortex computations

Abstract The movement of oil slicks on open waters has been predicted, using both deterministic and stochastic methods. The first method, named slick rose, consists in locating an area specifying the position of the slick during the first hours after the spill. The second method combines a deterministic approach for the simulation of current parameters to a stochastic method simulating the wind parameters. A Markov chain of the first order followed by a Monte Carlo approach enables the simulation of both phenomena. The third method presented in this paper describes a mass balance on the spilt oil, solved by the method of finite elements. The three methods are complementary to each other and constitute an important point for a contingency plan.

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Effects of plasma turbulence on the nonlinear evolution of magnetic island in tokamak

Nature Communications ◽

10.1038/s41467-020-20652-9 ◽

2021 ◽

Vol 12 (1) ◽

Cited By ~ 1

Author(s):

Minjun J. Choi ◽

Lāszlo Bardōczi ◽

Jae-Min Kwon ◽

T. S. Hahm ◽

Hyeon K. Park ◽

...

Keyword(s):

Magnetic Field ◽

Nonlinear Evolution ◽

Plasma Turbulence ◽

Magnetized Plasmas ◽

Tokamak Plasmas ◽

Magnetic Islands ◽

Magnetic Island ◽

Reconnection Site ◽

Ambient Turbulence

AbstractMagnetic islands (MIs), resulting from a magnetic field reconnection, are ubiquitous structures in magnetized plasmas. In tokamak plasmas, recent researches suggested that the interaction between an MI and ambient turbulence can be important for the nonlinear MI evolution, but a lack of detailed experimental observations and analyses has prevented further understanding. Here, we provide comprehensive observations such as turbulence spreading into an MI and turbulence enhancement at the reconnection site, elucidating intricate effects of plasma turbulence on the nonlinear MI evolution.

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Spatiotemporal Correlations in the Power Output of Wind Farms: On the Impact of Atmospheric Stability

Energies ◽

10.3390/en12081486 ◽

2019 ◽

Vol 12 (8) ◽

pp. 1486 ◽

Cited By ~ 2

Author(s):

Nicolas Tobin ◽

Adam Lavely ◽

Sven Schmitz ◽

Leonardo P. Chamorro

Keyword(s):

Power Output ◽

Wind Farm ◽

Statistical Significance ◽

Atmospheric Stability ◽

Wind Farms ◽

Temporal Correlations ◽

Theoretical Predictions ◽

Power Variance ◽

Ambient Turbulence ◽

The Impact

The dependence of temporal correlations in the power output of wind-turbine pairs on atmospheric stability is explored using theoretical arguments and wind-farm large-eddy simulations. For this purpose, a range of five distinct stability regimes, ranging from weakly stable to moderately convective, were investigated with the same aligned wind-farm layout used among simulations. The coherence spectrum between turbine pairs in each simulation was compared to theoretical predictions. We found with high statistical significance (p < 0.01) that higher levels of atmospheric instability lead to higher coherence between turbines, with wake motions reducing correlations up to 40%. This is attributed to higher dominance of atmospheric motions over wakes in strongly unstable flows. Good agreement resulted with the use of an empirical model for wake-added turbulence to predict the variation of turbine power coherence with ambient turbulence intensity (R 2 = 0.82), though other empirical relations may be applicable. It was shown that improperly accounting for turbine–turbine correlations can substantially impact power variance estimates on the order of a factor of 4.

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