Dynamics Of Large-scale Structures Research Articles

Размежевание или сплочение? (Динамика сетевой структуры политических телеграм-каналов: моделирование и эмпирический анализ)

In this paper, the authors propose novel methodology to analyze the dynamics of large-scale online network structures caused by significant exogenous shocks (foreign policy crises and the onset of military conflicts). The article focuses on diagnosing cohesion or polarization processes. As a first step, on the basis of the existing theoretical traditions, the authors analyze mechanisms at the micro-level that may lead to consolidation or polarization. Among these, they reveal mechanisms based on changes in position and mechanisms based on changes in identity. As a second step, the authors determine the “network projection” of these mechanisms’ actions: the changes in the structures of interaction networks between individuals they lead to. At this point mathematical modeling plays a key role, allowing for specific predictions regarding network behavior, expressed in changes in observable metrics. Four network indicators are proposed: the number of communities (clusters), modularity, the number of connections, and the average degree of nodes. As a result of computational experiments, the expected dynamics of all the indicators is calculated, which is compared with the corresponding mechanisms of changes in political positions or identity. As a third step, these predictions are compared with the indicators calculated from the empirical data. For the empirical analysis the article uses messages from the Russianlanguage political and news telegram channels, corresponding in time to the start of a special military operation (February-March, 2022), and those that chronologically occur 10 months earlier or later (April, 2021, and December, 2022). The general sample of such messages contains those with hyperlinks to other channels. It is the presence of such hyperlinks is considered to be a sign of the connection and is used to build a network. For each time period, the same network parameters are measured as for the computational data. Comparison of the observed dynamics with what is predicted by the models indicates that in the case of the special military operation, one key mechanism was at work — cohesion through the expansion of in-group boundaries, based on shifting to higher-order identity categories.

Secondary flow and thermal field dynamics in a T-junction with an upstream elbow: A POD-aided, eddy-sensitized Reynolds-stress modeling study

The thermal mixing of the flow-crossing streams in a T-shaped pipe junction configuration with the main branch inflow forming an elbow is presently simulated by applying a RANS-based eddy-resolving model of turbulence. The low-temperature main stream enters the T-junction with a Reynolds number of Rem=107893 after passing through a 90o-turned elbow located upstream. The high temperature branch stream is injected perpendicularly into the main stream at a Reynolds number of Rem=5422. A significant difference between the flow velocities of the two streams leads to the formation of a characteristic mixing process resembling a reattached jet configuration. Of particular interest is the interference of the branch flow with the main flow characterized by secondary vortices – the so – called Dean vortices, that are convected from the curved main inlet generating a low-rank mixing structures in its wake. The reference LES-based (Large-Eddy Simulation) database is provided by Tunstall et al. (2016). The computational framework relying on the scale-adaptive turbulence modeling approach, introduced principally by Menter and Egorov (2010), is used to simulate the dynamics of large-scale turbulent structures with moderate spatial and temporal resolution requirements. The motion of unresolved subscale structures is described by an appropriately sensitized differential near-wall Reynolds stress model according to Jakirlić and Maduta (2015). In addition, Proper-Orthogonal Decomposition (POD) is used to analyze the prevailing flow and thermal field mechanisms. The results obtained show a reasonable level of agreement with the LES reference, both from the standpoint of first-order statistics and spectral reproduction of the dynamics of coherent structures.

Flow dynamics of an axisymmetric impinging jet under two-frequency external forcing. A study by time-resolved PIV and DMD

The present paper reports on the experimental study of the dynamics of large-scale vortex structures in an axisymmetric impinging jet forced periodically with amplitude modulation. The velocity field measurements are conducted by the particle image velocimetry method. IR imaging is applied to evaluate the effect of external perturbations on local heat transfer coefficient. The Reynolds number of the jet flow is 12,500 and the distance between the nozzle and flat impingement plate is two nozzle diameters. The amplitude modulation corresponds to two-frequency forcing with a main harmonic (for the Strouhal number 0.5) and different sub-harmonics. To analyze quasi-periodic formation and near-wall merging of primary vortex structures and induced secondary vortices in the near-wall boundary layer, the obtained time-resolved velocity data sets are processed by the dynamic mode decomposition method. It is shown that the amplitude modulation can be efficiently used to attenuate the strength of the forced vortices due to the produced blowing events with different momenta and to control vortices pairing process in the near-wall region. It is also shown that two-frequency forcing can provide slightly greater intensification of heat transfer around the stagnation point with considerably smaller energy, consumed during the forcing.

Effects of optimisation parameters on data-driven magnetofrictional modelling of active regions

Context. The solar magnetic field plays an essential role in the formation, evolution, and dynamics of large-scale eruptive structures in the corona. The estimation of the coronal magnetic field, the ultimate driver of space weather, particularly in the ‘low’ and ‘middle’ corona, is presently limited due to practical difficulties. Data-driven time-dependent magnetofrictional modelling (TMFM) of active region magnetic fields has been proven to be a useful tool to study the corona. The input to the model is the photospheric electric field that is inverted from a time series of the photospheric magnetic field. Constraining the complete electric field, that is, including the non-inductive component, is critical for capturing the eruption dynamics. We present a detailed study of the effects of optimisation of the non-inductive electric field on the TMFM of AR 12473. Aims. We aim to study the effects of varying the non-inductive electric field on the data-driven coronal simulations, for two alternative parametrisations. By varying parameters controlling the strength of the non-inductive electric field, we wish to explore the changes in flux rope formation and their early evolution and other parameters, for instance, axial flux and magnetic field magnitude. Methods. We used the high temporal and spatial resolution cadence vector magnetograms from the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO). The non-inductive electric field component in the photosphere is critical for energising and introducing twist to the coronal magnetic field, thereby allowing unstable configurations to be formed. We estimated this component using an approach based on optimising the injection of magnetic energy. Results. Our data show that flux ropes are formed in all of the simulations except for those with the lower values of these optimised parameters. However, the flux rope formation, evolution and eruption time varies depending on the values of the optimisation parameters. The flux rope is formed and has overall similar evolution and properties with a large range of non-inductive electric fields needed to determine the non-inductive electric field component that is critical for energising and introducing twist to the coronal magnetic field. Conclusions. This study shows that irrespective of non-inductive electric field values, flux ropes are formed and erupted, which indicates that data-driven TMFM can be used to estimate flux rope properties early in their evolution without needing to employ a lengthy optimisation process.

Global insight into a complex-structured heliosphere based on the local multi-point analysis

From 29 January to 7 February 2022, the heliosphere was structured with large-scale interacting substructures that appeared with significant dissimilarities at distant observations separated longitudinally by ∼34°. Probing the complexity of the structured heliosphere with multi-point in situ and imaging observations by using a fleet of spacecraft has revealed many unknown facts on the dynamics of large-scale structures in the heliosphere. In this paper, we investigate a complex-structured heliosphere by analyzing the Sun, solar corona, and solar wind with remote and in situ observations aided by heliospheric modeling. We identified multiple flux ropes (FRs) associated with large expulsions of magnetized plasma-coronal mass ejections, from the same solar source in a three-day interval, an interplanetary wave shock, and a sheath in front of the FRs. In situ observations displayed a stream interaction region behind FRs formed due to the overtaking of different-speed solar winds. This high-speed stream originated from a coronal hole located southeast of the coronal mass ejection solar source. We find evidence of merging FRs, FR deflection due to the presence of the nearby coronal hole, and FR’s unalike structural appearance at distant multi-point observations obtained at 1 au. This complex-structured heliosphere resulted in multiple G1-class geomagnetic storms when interacting with Earth’s magnetosphere. Thus, the study focuses on the reconstruction of the structured heliosphere based on observations and modeling. It highlights the importance of multi-point observations in understanding the global configuration and disparity in the local nature of a structured heliosphere.

Experimental investigation of dynamics of large-scale vortex structures of a sweeping jet emitted into a slot channel

Experimental investigation of dynamics of large-scale vortex structures of a sweeping jet emitted into a slot channel

Experimental study of coherent wall-pressure fluctuations associated with the turbulent near wake of a cylinder

The objective of this work is to present a coherent detection method to determine relationships between pressure fluctuations and wake velocity in the case of the flow past a cylinder in a turbulent regime. We report experimental results and pressure–velocity statistics measured simultaneously on the surface boundary layer and the near wake in the range of Reynolds numbers (2×103<Re<3.5×104). The novelty of the analysis lies in the application of a coherent mean method to determine conditioned wall pressure statistics to velocity events observed in the turbulent cylinder wake. The method allows one to associate wake turbulent events with a corresponding wall-pressure signal profile on the cylinder surface performing discrete angular measurements with a minimum number of pressure sensors. Simultaneous measurements of both time series of wake velocity and wall pressure allow us to characterize the mutual influence of hydrodynamic perturbations from the boundary layer surface pressure with the near wake velocity fluctuations. Large scale turbulent vortex shedding is well correlated with surface pressure fluctuations as expected in the low frequency range. Near wake velocity signals were used as timing signals to determine the coherent influence of a representative velocity pattern on the statistical properties of wall pressure fluctuations. The dynamics of low-frequency large-scale structures is consistent with the presence of counter-rotating vortices and is well correlated with a great part of the pressure fluctuations of the boundary layer. Conditional statistics using the velocity pattern obtained from the coherent averaging method provided the instantaneous pressure fluctuating profile associated with the large-scale vortex shedding cycle, thus, enabling a coherent estimation of the fluctuating lift and drag forces. Conditional statistics on wake velocity are well influenced by the phase of the vortex life-cycle.

Dynamics of Large-Scale Industry Structures in the Context of the Territories of Advanced Socio-Economic Development and Digitalization

Dynamics of Large-Scale Industry Structures in the Context of the Territories of Advanced Socio-Economic Development and Digitalization

Transitions of turbulent superstructures in generalized Kolmogorov flow

Self-organized large-scale flow structures occur in a wide range of turbulent flows. Yet, their emergence, dynamics, and interplay with small-scale turbulence are not well understood. Here, we investigate such self-organized turbulent superstructures in three-dimensional turbulent Kolmogorov flow with large-scale drag. Through extensive simulations, we uncover their low-dimensional dynamics featuring transitions between several stable and meta-stable large-scale structures as a function of the damping parameter. The main dissipation mechanism for the turbulent superstructures is the generation of small-scale turbulence, whose local structure depends strongly on the large-scale flow. Our results elucidate the generic emergence and low-dimensional dynamics of large-scale flow structures in fully developed turbulence and reveal a strong coupling of large- and small-scale flow features.

Compressibility Effects on Large Structures and Entrainment Length Scales in Mixing Layers

In this work, three-component planar velocity measurements are analyzed to identify the effects of compressibility on mixing layer turbulence, with a focus on the evolution of large-scale structures, dominant spatial eigenmodes, and entrainment length scales. Velocity measurements obtained via stereoscopic particle image velocimetry for five different dual-stream air planar mixing layers with convective Mach numbers of , 0.38, 0.55, 0.69, and 0.88 are analyzed. Results of two-point correlations reveal that length scales of the streamwise velocity fluctuations increase in both the streamwise and transverse directions, whereas the length scales of the transverse velocity fluctuations decrease in the transverse direction. To further investigate these trends, the spatial organization, shape, and dynamics of large-scale turbulent structures are examined via two-dimensional spatial velocity correlations, proper orthogonal decomposition, and linear stochastic estimation. These quantitative techniques support qualitative findings in the literature that report coherent, round roller structures in incompressible mixing layers becoming flattened and elongated longitudinally with increased compressibility. This evolution is likely due to a dominant pulsing motion present for the higher cases and can be linked to compressibility effects on the entrainment mechanisms. Length scales of entrainment are determined using autocorrelations of normal flow velocity components along instantaneously identified turbulent/non-turbulent interfaces and are found to decrease with increasing . This result can heuristically be interpreted as small-scale nibbling being dominant for higher , whereas larger-scale engulfment contributes more in nearly incompressible mixing layers.

Temporal dynamics of large-scale structures for turbulent Rayleigh–Bénard convection in a moderate aspect-ratio cylinder

Abstract

Projection of the gravitational dynamics on a subspace of probability distributions: Curl-free Gaussian Ansatz

We present a new approach to model the gravitational dynamics of large-scale structures. Instead of solving the equations of motion up to a finite perturbative order or building phenomenological models, we follow the evolution of the probability distribution of the displacement and velocity fields within an approximation subspace. Keeping the exact equations of motion with their full nonlinearity, this provides a nonperturbative scheme that goes beyond shell crossing. Focusing on the simplest case of a curl-free Gaussian Ansatz for the displacement and velocity fields, we find that truncations of the power spectra on nonlinear scales directly arise from the equations of motion. This leads to a truncated Zeldovich approximation for the density power spectrum, but with a truncation that is not set a priori and with different power spectra for the displacement and velocity fields. The positivity of their autopower spectra also follows from the equations of motion. Although the density power spectrum is only recovered up to a smooth drift on baryon acoustic oscillation (BAO) scales, the predicted density correlation function agrees with numerical simulations within 2% from BAO scales down to $7{h}^{\ensuremath{-}1}\text{ }\text{ }\mathrm{Mpc}$ at $z\ensuremath{\ge}0.35$, without any free parameter. Thus, this parameter-free extension of the Zeldovich approximation is not competitive with other schemes for the power spectrum, but it provides a good prediction for the correlation function. However, the improvement over the standard Zeldovich approximation remains rather modest. This means that including non-Gaussianities will be essential to significantly improve analytical predictions within this general framework.

Dynamics of Large Scale Turbulence in Finite-Sized Wind Farm Canopy Using Proper Orthogonal Decomposition and a Novel Fourier-POD Framework

Large scale coherent structures in the atmospheric boundary layer (ABL) are known to contribute to the power generation in wind farms. In order to understand the dynamics of large scale structures, we perform proper orthogonal decomposition (POD) analysis of a finite sized wind turbine array canopy in the current paper. The POD analysis sheds light on the dynamics of large scale coherent modes as well as on the scaling of the eigenspectra in the heterogeneous wind farm. We also propose adapting a novel Fourier-POD (FPOD) modal decomposition which performs POD analysis of spanwise Fourier-transformed velocity. The FPOD methodology helps us in decoupling the length scales in the spanwise and streamwise direction when studying the 3D energetic coherent modes. Additionally, the FPOD eigenspectra also provide deeper insights for understanding the scaling trends of the three-dimensional POD eigenspectra and its convergence, which is inherently tied to turbulent dynamics. Understanding the behaviour of large scale structures in wind farm flows would not only help better assess reduced order models (ROM) for forecasting the flow and power generation but would also play a vital role in improving the decision making abilities in wind farm optimization algorithms in future. Additionally, this study also provides guidance for better understanding of the POD analysis in the turbulence and wind farm community.

Cessation and reversals of large-scale structures in square Rayleigh–Bénard cells

We consider direct numerical simulations of turbulent Rayleigh–Bénard convection inside two-dimensional square cells. For Rayleigh numbers $Ra=10^{6}$ to $Ra=5\times 10^{8}$ and Prandtl numbers $Pr=3$ and $Pr=4.3$, two types of flow regimes are observed intermittently: consecutive flow reversals (CR), and extended cessations (EC). For each regime, we combine proper orthogonal decomposition (POD) and statistical tools on long-term data to characterise the dynamics of large-scale structures. For the CR regime, centrosymmetric modes are dominant and display a coherent dynamics, while non-centrosymmetric modes fluctuate randomly. For the EC regime, all POD modes follow Poissonian statistics and a non-centrosymmetric mode is dominant. To explore further the differences between the CR and EC regimes, an analysis based on a cluster partition of the POD phase space is proposed. This data-driven approach confirms the successive mechanisms of the generic reversal cycle in CR as proposed in Castillo-Castellanos et al. (J. Fluid Mech., vol. 808, 2016, pp. 614–640). However, these mechanisms may take one of multiple paths in the POD phase space. Inside the EC regime, this approach reveals the presence of two types of coherent time sequences (weak reversals and actual cessations) and more rarely intense plume crossings. Finally, we analyse within a range of Rayleigh numbers up to turbulent flow, the relation between dynamical regimes and the POD energetic contents as well as the residence time in each cluster.

A versatile taxonomy of low-dimensional vortex models for unsteady aerodynamics

Inviscid vortex models have been demonstrated to capture the essential physics of massively separated flows past aerodynamic surfaces, but they become computationally expensive as coherent vortex structures are formed and the wake is developed. In this work, we present a two-dimensional vortex model in which vortex sheets represent shear layers that separate from sharp edges of the body and point vortices represent the rolled-up cores of these shear layers and the other coherent vortices in the wake. We develop a circulation transfer procedure that enables each vortex sheet to feed its circulation into a point vortex instead of rolling up. This procedure reduces the number of computational elements required to capture the dynamics of vortex formation while eliminating the spurious force that manifests when transferring circulation between vortex elements. By tuning the rate at which the vortex sheets are siphoned into the point vortices, we can adjust the balance between the model’s dimensionality and dynamical richness, enabling it to span the entire taxonomy of inviscid vortex models. This hybrid model can capture the development and subsequent shedding of the starting vortices with insignificant wall-clock time and remain sufficiently low-dimensional to simulate long-time-horizon events such as periodic bluff-body shedding. We demonstrate the viability of the method by modelling the impulsive translation of a wing at various fixed angles of attack, pitch-up manoeuvres that linearly increase the angle of attack from$0^{\circ }$to$90^{\circ }$, and oscillatory pitching and heaving. We show that the proposed model correctly predicts the dynamics of large-scale vortical structures in the flow by comparing the distributions of vorticity and force responses from results of the proposed model with a model using only vortex sheets and, in some cases, high-fidelity viscous simulation.

Large-scale coherent flow structures in rough-bed open-channel flow observed in fluctuations of three-dimensional velocity, skin friction and bed pressure

ABSTRACTThe dynamics of large-scale coherent structures (LSCS) are investigated in a rough-bed flow over the whole water column and longitudinal and transverse turbulent fluxes of momentum are compared. The relation between LSCS and fluctuations of skin friction and near-bed surface pressure is examined in order to understand the effects of LSCS on the bed. The study was carried out in an open channel with a non-moving permeable bed of screeded loose-mixed gravel (D50 = 1.5 cm) at Reynolds numbers ranging from 3.19 × 104 to 1.08 × 105. Quasi-instantaneous full-depth three-dimensional (3D) velocity profiles with high spatial and temporal resolution measured with an acoustic Doppler velocity profiler (ADVP) are combined with the signals of a hot-film sensor mounted on the top of the gravel and a piezoresistive pressure transducer placed in the top layer of the bed particles at the centre of the channel. Vertical turbulent momentum flux is clearly dominated by ejections and sweeps over most of the water column. Near the bed, contributions of sweeps are larger than those of ejections. This is reversed at the mid-depth (z/h = 0.5). No preferential quadrant orientation is seen for the transverse momentum flux. A correlation between LSCS dynamics in the water column and data from the sensors on the bed is made evident. Sweeps correlate with positive fluctuations of bottom pressure and skin friction while ejections correlate with negative ones.

Dynamics of Large-scale Coronal Structures as Imaged during the 2012 and 2013 Total Solar Eclipses

Abstract White light images acquired at the peak of solar activity cycle 24, during the total solar eclipses of 2012 November 13 and 2013 November 3, serendipitously captured erupting prominences accompanied by CMEs. Application of state-of-the-art image processing techniques revealed the intricate details of two “atypical” large-scale structures, with strikingly sharp boundaries. By complementing the processed white light eclipse images with processed images from co-temporal Solar Dynamics Observatory/AIA and SOHO/LASCO observations, we show how the shape of these atypical structures matches the shape of faint CME shock fronts, which traversed the inner corona a few hours prior to the eclipse observations. The two events were not associated with any prominence eruption but were triggered by sudden brightening events on the solar surface accompanied by sprays and jets. The discovery of the indelible impact that frequent and innocuous transient events in the low corona can have on large-scale coronal structures was enabled by the radial span of the high-resolution white light eclipse images, starting from the solar surface out to several solar radii, currently unmatched by any coronagraphic instrumentation. These findings raise the interesting question as to whether large-scale coronal structures can ever be considered stationary. They also point to the existence of a much larger number of CMEs that goes undetected from the suite of instrumentation currently observing the Sun.

Chaotic dynamics of large-scale structures in a turbulent wake

The dynamics of a 3D bimodal turbulent wake downstream a square-back Ahmed body are experimentally studied in a wind-tunnel through high-frequency wall pressure probes mapping the rear of the model and a horizontal 2D velocity field. The barycenters of the pressure distribution over the rear part of the model and the intensity recirculation are found highly correlated. Both described the most energetic large-scale structures dynamics, confirming the relation between the large-scale recirculation bubble and its wall pressure foot-print. Focusing on the pressure, its barycenter trajectory has a stochastic behavior but its low frequencies dynamics exhibit the same characteristics as a weak strange chaotic attractor system, with two well defined attractors. The low frequencies dynamics associated to the large-scale structures are then analyzed. The largest Lyapunov exponent is first estimated, leading to a low positive value characteristic of strange attractors and weak chaotic systems. Afterwards, analyzing the autocorrelation function of the time-series, we compute the correlation dimension, larger than two. The signal is finally transformed and analyzed as a telegraph signal showing that its dynamics correspond to a quasi-random telegraph signal. This is the first demonstration that the low frequencies dynamics of a turbulent 3D wake are not a purely stochastic process but rather a weak chaotic process exhibiting strange attractors. From the flow-control point of view, it also opens the path to more simple closed-loop flow control strategies aiming at the stabilization of the wake and the control of the dynamics of the wake barycenter.

Ability of a low-dimensional model to predict geometry-dependent dynamics of large-scale coherent structures in turbulence.

We test the ability of a general low-dimensional model for turbulence to predict geometry-dependent dynamics of large-scale coherent structures, such as convection rolls. The model consists of stochastic ordinary differential equations, which are derived as a function of boundary geometry from the Navier-Stokes equations [Brown and Ahlers, Phys. Fluids 20, 075101 (2008); Phys. Fluids 20, 105105 (2008)]. We test the model using Rayleigh-Bénard convection experiments in a cubic container. The model predicts a mode in which the alignment of a convection roll stochastically crosses a potential barrier to switch between diagonals. We observe this mode with a measured switching rate within 30% of the prediction.

Nonlinear dynamics of large-scale coherent structures in turbulent free shear layers

Fully developed turbulent free shear layers exhibit a high degree of order, characterized by large-scale coherent structures in the form of spanwise vortex rollers. Extensive experimental investigations show that such organized motions bear remarkable resemblance to instability waves, and their main characteristics, including the length scales, propagation speeds and transverse structures, are reasonably well predicted by linear stability analysis of the mean flow. In this paper, we present a mathematical theory to describe the nonlinear dynamics of coherent structures. The formulation is based on the triple decomposition of the instantaneous flow into a mean field, coherent fluctuations and small-scale turbulence but with the mean-flow distortion induced by nonlinear interactions of coherent fluctuations being treated as part of the organized motion. The system is closed by employing a gradient type of model for the time- and phase-averaged Reynolds stresses of fine-scale turbulence. In the high-Reynolds-number limit, the nonlinear non-equilibrium critical-layer theory for laminar-flow instabilities is adapted to turbulent shear layers by accounting for (1) the enhanced non-parallelism associated with fast spreading of the mean flow, and (2) the influence of small-scale turbulence on coherent structures. The combination of these factors with nonlinearity leads to an interesting evolution system, consisting of coupled amplitude and vorticity equations, in which non-parallelism contributes the so-called translating critical-layer effect. Numerical solutions of the evolution system capture vortex roll-up, which is the hallmark of a turbulent mixing layer, and the predicted amplitude development mimics the qualitative feature of oscillatory saturation that has been observed in a number of experiments. A fair degree of quantitative agreement is obtained with one set of experimental data.