Testing for Markovian character and modeling of intermittency in solar wind turbulence

Strumik, M.; Macek, Wiesław M.

doi:10.1103/physreve.78.026414

Cited by 29 publications

(30 citation statements)

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“…However, the T ub and T bu transfer functions were also observed to be local, with most of the transfer between the velocity and the magnetic field taking place between the same shell. The remaining transfer (for non-neighboring shells) was observed to decay more slowly than in the T uu and T bb functions, but except for this detail no other indications of non-locality were reported.Similar results were obtained from analysis of solar wind turbulence(Strumik & Macek 200 Solar wind turbulence is often considered the MHD equivalent of hydrodynamic freely decaying wind tunnel turbulence (see Bruno & Carbone 2005 for a review).From 1996 Ulysses magnetometers time series and using a Markov process ap-proach,Strumik & Macek (2008b) concluded that the transfer of magnetic to magnetic energy was local. Then, using velocity and magnetic field time series from ACE spacecraft from 1999 to 2006 and performing the same analysis on the remaining transfers they concluded that all transfers were local.…”

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confidence: 56%

Scale Interactions in Magnetohydrodynamic Turbulence

Mininni

2011

Annu. Rev. Fluid Mech.

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This article reviews recent studies of scale interactions in magnetohydrodynamic turbulence. The present day increase of computing power, which allows for the exploration of different configurations of turbulence in conducting flows, and the development of shell-toshell transfer functions, has led to detailed studies of interactions between the velocity and the magnetic field and between scales. In particular, processes such as induction and dynamo action, the damping of velocity fluctuations by the Lorentz force, or the development of anisotropies, can be characterized at different scales. In this context we consider three different configurations often studied in the literature: mechanically forced turbulence, freely decaying turbulence, and turbulence in the presence of a uniform magnetic field. Each configuration is of interest for different geophysical and astrophysical applications. Local and non-local transfers are discussed

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confidence: 56%

Scale Interactions in Magnetohydrodynamic Turbulence

Mininni

2011

Annu. Rev. Fluid Mech.

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“…The s * peculiar polarization might be associated with a horizontal current system flowing at the ground, switched on by an anomalous ground impedance generated by the fault break. It is thought that the low-frequency components (ULF/ELF) of seismo-electromagnetic emission (SEME) waves generated by pre-seismic sources (such as local deformation of fields, rock dislocation and micro-fracturing, gas emission, fluid diffusion, charged particle generation and motion, electrokinetic, piezo-magnetic and piezoelectric effects, and fair weather currents) are transmitted into the near-Earth space (Dobrovolsky, 1989;Teisseyre, 1997;Pulinets and Kirill, 2004;Sorokin, 2001). During their propagation through the solid crust, the SEME waves characterized by lower periods are attenuated.…”

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confidence: 99%

Electromagnetic field observations by the DEMETER satellite in connection with the 2009 L'Aquila earthquake

et al. 2018

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Abstract. To define a background in the electromagnetic emissions above seismic regions, it is necessary to define the statistical distribution of the wave energy in the absence of seismic activity and any other anomalous input (e.g. solar forcing). This paper presents a completely new method to determine both the environmental and instrumental backgrounds applied to the entire DEMETER satellite electric and magnetic field data over L'Aquila. Our technique is based on a new data analysis tool called ALIF (adaptive local iterative filtering, Cicone et al., 2016; Cicone and Zhou, 2017; Piersanti et al., 2017b). To evaluate the instrumental background, we performed a multiscale statistical analysis in which the instantaneous relative energy (ϵrel), kurtosis, and Shannon entropy were calculated. To estimate the environmental background, a map, divided into 1∘×1∘ latitude–longitude cells, of the averaged relative energy (ϵrel‾), has been constructed, taking into account the geomagnetic activity conditions, the presence of seismic activity, and the local time sector of the satellite orbit. Any distinct signal different (over a certain threshold) from both the instrumental and environmental backgrounds will be considered as a case event to be investigated. Interestingly, on 4 April 2009, when DEMETER flew exactly over L'Aquila at UT = 20:29, an anomalous signal was observed at 333 Hz on both the electric and magnetic field data, whose characteristics seem to be related to pre-seismic activity.

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“…For a valid spatial Markov process two assumptions must hold: (1) The spatial correlation structure must be statistically stationary and (2) the particles next to the velocity state depends solely on the current state (Renner et al, 2001a(Renner et al, , 2001bStrumik & Macek, 2008;Sund et al, 2017b). In this study we follow the methodology of Sund et al (2016) and define the scale over which these two assumptions are valid by making use of a less commonly used metric-the autocorrelation K of the particles' velocity along the trajectory,…”

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confidence: 99%

Trajectories as Training Images to Simulate Advective‐Diffusive, Non‐Fickian Transport

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Bolster

Bijeljic

et al. 2019

Water Resources Research

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We propose a spatial Markov model to simulate transport in three‐dimensional complex porous media flows. Our methodology is inspired by the concept of training images from geostatistics. Instead of using a training image we use highly resolved training trajectories obtained by high‐resolution particle tracking, from which we sample increments in our random walk model. To reflect higher‐order processes, subsequent increments are correlated. The approach can be split into three steps. First, we subdivide (cut) the training trajectories to form an archive of trajectory segments. Next, we recursively sample segments, where subsequent samples are chosen conditioned to the previous one to ensure continuity and smoothness of velocity (conditional copy). Finally, we merge (paste) consecutive segments together to generate simulated trajectories of arbitrary length. This training trajectory approach aims to overcome three common shortcomings of spatial Markov models: (1) We simulate finite‐Péclet transport in three dimensions without commonly made simplifications (e.g., dimensionality reduction, and neglecting diffusion). (2) We do not parameterize dependence via a high‐dimensional transition matrix. (3) We simulate transport at the resolution of the (highly resolved) training trajectories, which can be important for processes such as mixing and reaction. To validate our methodology, we apply it to simulate transport within a three‐dimensional sandstone sample and compare predictions of a broad range of benchmark metrics against measurements from direct numerical simulations. We demonstrate that the training trajectories approach accurately represents three‐dimensional particle motion, suggesting that this method can capture the governing dependence structure and simulate transport processes in full complexity.

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Testing for Markovian character and modeling of intermittency in solar wind turbulence

Cited by 29 publications

References 29 publications

Scale Interactions in Magnetohydrodynamic Turbulence

Scale Interactions in Magnetohydrodynamic Turbulence

Electromagnetic field observations by the DEMETER satellite in connection with the 2009 L'Aquila earthquake

Trajectories as Training Images to Simulate Advective‐Diffusive, Non‐Fickian Transport

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