The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform
John O Dabiri - One of the best experts on this subject based on the ideXlab platform.
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simultaneous Coherent Structure coloring facilitates interpretable clustering of scientific data by amplifying dissimilarity
PLOS ONE, 2019Co-Authors: Brooke E Husic, Kristy L Schlueterkuck, John O DabiriAbstract:The clustering of data into physically meaningful subsets often requires assumptions regarding the number, size, or shape of the subgroups. Here, we present a new method, simultaneous Coherent Structure coloring (sCSC), which accomplishes the task of unsupervised clustering without a priori guidance regarding the underlying Structure of the data. sCSC performs a sequence of binary splittings on the dataset such that the most dissimilar data points are required to be in separate clusters. To achieve this, we obtain a set of orthogonal coordinates along which dissimilarity in the dataset is maximized from a generalized eigenvalue problem based on the pairwise dissimilarity between the data points to be clustered. This sequence of bifurcations produces a binary tree representation of the system, from which the number of clusters in the data and their interrelationships naturally emerge. To illustrate the effectiveness of the method in the absence of a priori assumptions, we apply it to three exemplary problems in fluid dynamics. Then, we illustrate its capacity for interpretability using a high-dimensional protein folding simulation dataset. While we restrict our examples to dynamical physical systems in this work, we anticipate straightforward translation to other fields where existing analysis tools require ad hoc assumptions on the data Structure, lack the interpretability of the present method, or in which the underlying processes are less accessible, such as genomics and neuroscience.
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model parameter estimation using Coherent Structure colouring
Journal of Fluid Mechanics, 2019Co-Authors: Kristy L Schlueterkuck, John O DabiriAbstract:Lagrangian data assimilation is a complex problem in oceanic and atmospheric modelling. Tracking drifters in large-scale geophysical flows can involve uncertainty in drifter location, complex inertial effects and other factors which make comparing them to simulated Lagrangian trajectories from numerical models extremely challenging. Temporal and spatial discretisation, factors necessary in modelling large scale flows, also contribute to separation between real and simulated drifter trajectories. The chaotic advection inherent in these turbulent flows tends to separate even closely spaced tracer particles, making error metrics based solely on drifter displacements unsuitable for estimating model parameters. We propose to instead use error in the Coherent Structure colouring (CSC) field to assess model skill. The CSC field provides a spatial representation of the underlying Coherent patterns in the flow, and we show that it is a more robust metric for assessing model accuracy. Through the use of two test cases, one considering spatial uncertainty in particle initialisation, and one examining the influence of stochastic error along a trajectory and temporal discretisation, we show that error in the Coherent Structure colouring field can be used to accurately determine single or multiple simultaneously unknown model parameters, whereas a conventional error metric based on error in drifter displacement fails. Because the CSC field enhances the difference in error between correct and incorrect model parameters, error minima in model parameter sweeps become more distinct. The effectiveness and robustness of this method for single and multi-parameter estimation in analytical flows suggest that Lagrangian data assimilation for real oceanic and atmospheric models would benefit from a similar approach.
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identification of individual Coherent sets associated with flow trajectories using Coherent Structure coloring
Chaos, 2017Co-Authors: Kristy L Schlueterkuck, John O DabiriAbstract:We present a method for identifying the Coherent Structures associated with individual Lagrangian flow trajectories even where only sparse particle trajectory data are available. The method, based on techniques in spectral graph theory, uses the Coherent Structure Coloring vector and associated eigenvectors to analyze the distance in higher-dimensional eigenspace between a selected reference trajectory and other tracer trajectories in the flow. By analyzing this distance metric in a hierarchical clustering, the Coherent Structure of which the reference particle is a member can be identified. This algorithm is proven successful in identifying Coherent Structures of varying complexities in canonical unsteady flows. Additionally, the method is able to assess the relative coherence of the associated Structure in comparison to the surrounding flow. Although the method is demonstrated here in the context of fluid flow kinematics, the generality of the approach allows for its potential application to other unsupervised clustering problems in dynamical systems such as neuronal activity, gene expression, or social networks.
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identification of individual Coherent sets associated with flow trajectories using Coherent Structure coloring
arXiv: Fluid Dynamics, 2017Co-Authors: Kristy L Schlueterkuck, John O DabiriAbstract:We present a method for identifying the Coherent Structures associated with individual Lagrangian flow trajectories even where only sparse particle trajectory data is available. The method, based on techniques in spectral graph theory, uses the Coherent Structure Coloring vector and associated eigenvectors to analyze the distance in higher-dimensional eigenspace between a selected reference trajectory and other tracer trajectories in the flow. By analyzing this distance metric in a hierarchical clustering, the Coherent Structure of which the reference particle is a member can be identified. This algorithm is proven successful in identifying Coherent Structures of varying complexities in canonical unsteady flows. Additionally, the method is able to assess the relative coherence of the associated Structure in comparison to the surrounding flow. Although the method is demonstrated here in the context of fluid flow kinematics, the generality of the approach allows for its potential application to other unsupervised clustering problems in dynamical systems such as neuronal activity, gene expression, or social networks.
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Coherent Structure coloring: identification of Coherent Structures from sparse data using graph theory
Journal of Fluid Mechanics, 2016Co-Authors: Kristy L. Schlueter-kuck, John O DabiriAbstract:We present a frame-invariant method for detecting Coherent Structures from Lagrangian flow trajectories that can be sparse in number, as is the case in many fluid mechanics applications of practical interest. The method, based on principles used in graph coloring and spectral graph drawing algorithms, examines a measure of the kinematic dissimilarity of all pairs of fluid trajectories, either measured experimentally, e.g. using particle tracking velocimetry; or numerically, by advecting fluid particles in the Eulerian velocity field. Coherence is assigned to groups of particles whose kinematics remain similar throughout the time interval for which trajectory data is available, regardless of their physical proximity to one another. Through the use of several analytical and experimental validation cases, this algorithm is shown to robustly detect Coherent Structures using significantly less flow data than is required by existing spectral graph theory methods.
Milan Svanda - One of the best experts on this subject based on the ideXlab platform.
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comparison of solar surface flows inferred from time distance helioseismology and Coherent Structure tracking using hmi sdo observations
The Astrophysical Journal, 2013Co-Authors: Milan Svanda, Raymond Burston, T. Roudier, Michel Rieutord, Laurent GizonAbstract:We compare measurements of horizontal flows on the surface of the Sun using helioseismic time-distance inversions and Coherent Structure tracking of solar granules. Tracking provides two-dimensional horizontal flows on the solar surface, whereas the time-distance inversions estimate the full three-dimensional velocity flows in the shallow near-surface layers. Both techniques use Helioseismic and Magnetic Imager observations as input. We find good correlations between the various measurements resulting from the two techniques. Further, we find a good agreement between these measurements and the time-averaged Doppler line-of-sight velocity, and also perform sanity checks on the vertical flow that resulted from the three-dimensional time-distance inversion.
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comparison of solar surface flows inferred from time distance helioseismology and Coherent Structure tracking using hmi sdo observations
arXiv: Solar and Stellar Astrophysics, 2013Co-Authors: Milan Svanda, Raymond Burston, T. Roudier, Michel Rieutord, Laurent GizonAbstract:We compare measurements of horizontal flows on the surface of the Sun using helioseismic time--distance inversions and Coherent Structure tracking of solar granules. Tracking provides 2D horizontal flows on the solar surface, whereas the time--distance inversions estimate the full 3-D velocity flows in the shallow near-surface layers. Both techniques use HMI observations as an input. We find good correlations between the various measurements resulting from the two techniques. Further, we find a good agreement between these measurements and the time-averaged Doppler line-of-sight velocity, and also perform sanity checks on the vertical flow that resulted from the 3-D time--distance inversion.
Shinichiro Toda - One of the best experts on this subject based on the ideXlab platform.
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Coherent Structure of zonal flow and onset of turbulent transport
Physics of Plasmas, 2005Co-Authors: Kimitaka Itoh, Klaus Hallatschek, Sanae-i. Itoh, Patrick Diamond, Shinichiro TodaAbstract:Excitation of the turbulence in the range of drift wave frequency and zonal flow in magnetized plasmas is analyzed. Nonlinear stabilization effect on zonal flow drive is introduced, and the steady state solution is obtained. The condition for the onset of turbulent transport is obtained and partition ratio of fluctuation energy into turbulence and zonal flows is derived. The turbulent transport coefficient, which includes the effect of zonal flow, is also obtained. Analytic result and direct numerical simulation show a good agreement.
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Coherent Structure of Zonal Flow and Nonlinear Saturation
Journal of the Physical Society of Japan, 2004Co-Authors: Kimitaka Itoh, Klaus Hallatschek, Shinichiro Toda, Heiji Sanuki, Sanae-i. ItohAbstract:The nonlinear Structure of the zonal flow in toroidal plasma is investigated in the case that the autocorrelation times of drift waves are much shorter than the autocorrelation time of zonal flow. It is found that the turbulent drive of the zonal flow starts to decrease at a high velocity shear of the zonal flow. By this mechanism, the zonal flow evolves into a stable stationary Structure in turbulent plasmas. Flow velocity and radial wavelength are obtained.
Laurent Gizon - One of the best experts on this subject based on the ideXlab platform.
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comparison of solar surface flows inferred from time distance helioseismology and Coherent Structure tracking using hmi sdo observations
The Astrophysical Journal, 2013Co-Authors: Milan Svanda, Raymond Burston, T. Roudier, Michel Rieutord, Laurent GizonAbstract:We compare measurements of horizontal flows on the surface of the Sun using helioseismic time-distance inversions and Coherent Structure tracking of solar granules. Tracking provides two-dimensional horizontal flows on the solar surface, whereas the time-distance inversions estimate the full three-dimensional velocity flows in the shallow near-surface layers. Both techniques use Helioseismic and Magnetic Imager observations as input. We find good correlations between the various measurements resulting from the two techniques. Further, we find a good agreement between these measurements and the time-averaged Doppler line-of-sight velocity, and also perform sanity checks on the vertical flow that resulted from the three-dimensional time-distance inversion.
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comparison of solar surface flows inferred from time distance helioseismology and Coherent Structure tracking using hmi sdo observations
arXiv: Solar and Stellar Astrophysics, 2013Co-Authors: Milan Svanda, Raymond Burston, T. Roudier, Michel Rieutord, Laurent GizonAbstract:We compare measurements of horizontal flows on the surface of the Sun using helioseismic time--distance inversions and Coherent Structure tracking of solar granules. Tracking provides 2D horizontal flows on the solar surface, whereas the time--distance inversions estimate the full 3-D velocity flows in the shallow near-surface layers. Both techniques use HMI observations as an input. We find good correlations between the various measurements resulting from the two techniques. Further, we find a good agreement between these measurements and the time-averaged Doppler line-of-sight velocity, and also perform sanity checks on the vertical flow that resulted from the 3-D time--distance inversion.
Beverley Mckeon - One of the best experts on this subject based on the ideXlab platform.
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On Coherent Structure in wall turbulence
Journal of Fluid Mechanics, 2013Co-Authors: Ati S. Sharma, Beverley MckeonAbstract:A new theory of Coherent Structure in wall turbulence is presented. The theory is the first to predict packets of hairpin vortices and other Structure in turbulence, and their dynamics, based on an analysis of the Navier-Stokes equations, under an assumption of a turbulent mean profile. The assumption of the turbulent mean acts as a restriction on the class of possible Structures. It is shown that the Coherent Structure is a manifestation of essentially low-dimensional flow dynamics, arising from a critical layer mechanism. Using the decomposition presented in McKeon & Sharma (J. Fluid Mech, 658, 2010), complex Coherent Structure is recreated from minimal superpositions of response modes predicted by the analysis, which take the form of radially-varying travelling waves. By way of example, simple combinations of these modes are offered that predicts hairpins and modulated hairpin packets. The phase interaction also predicts important skewness and correlation results known in the literature. It is also shown that the very large scale motions act to organise hairpin-like Structures such that they co-locate with areas of low streamwise momentum, by a mechanism of locally varying the shear profile. The relationship between Taylor's hypothesis and coherence is discussed and both are shown to be the consequence of the localisation of the response modes around the critical layer. A pleasing link is made to the classical laminar inviscid theory, whereby the essential mechanism underlying the hairpin vortex is captured by two obliquely interacting Kelvin-Stuart (cat's eye) vortices. Evidence for the theory is presented based on comparison to observations of Structure reported in the experimental, transitional flow and turbulent flow numerical simulation literature.
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on Coherent Structure in wall turbulence
Journal of Fluid Mechanics, 2013Co-Authors: Ati S. Sharma, Beverley MckeonAbstract:A new theory of Coherent Structure in wall turbulence is presented. The theory is the first to predict packets of hairpin vortices and other Structure in turbulence, and their dynamics, based on an analysis of the Navier–Stokes equations, under an assumption of a turbulent mean profile. The assumption of the turbulent mean acts as a restriction on the class of possible Structures. It is shown that the Coherent Structure is a manifestation of essentially low-dimensional flow dynamics, arising from a critical-layer mechanism. Using the decomposition presented in McKeon & Sharma (J. Fluid Mech., vol. 658, 2010, pp. 336–382), complex Coherent Structure is recreated from minimal superpositions of response modes predicted by the analysis, which take the form of radially varying travelling waves. The leading modes effectively constitute a low-dimensional description of the turbulent flow, which is optimal in the sense of describing the resonant effects around the critical layer and which minimally predicts all types of Structure. The approach is general for the full range of scales. By way of example, simple combinations of these modes are offered that predict hairpins and modulated hairpin packets. The example combinations are chosen to represent observed Structure, consistent with the nonlinear triadic interaction for wavenumbers that is required for self-interaction of Structures. The combination of the three leading response modes at streamwise wavenumbers 6; 1; 7 and spanwise wavenumbers ±6; ±6; ±12, respectively, with phase velocity 2/3, is understood to represent a turbulence ‘kernel’, which, it is proposed, constitutes a self-exciting process analogous to the near-wall cycle. Together, these interactions explain how the mode combinations may self-organize and self-sustain to produce experimentally observed Structure. The phase interaction also leads to insight into skewness and correlation results known in the literature. It is also shown that the very large-scale motions act to organize hairpin-like Structures such that they co-locate with areas of low streamwise momentum, by a mechanism of locally altering the shear profile. These energetic streamwise Structures arise naturally from the resolvent analysis, rather than by a summation of hairpin packets. In addition, these packets are modulated through a ‘beat’ effect. The relationship between Taylor’s hypothesis and coherence is discussed, and both are shown to be the consequence of the localization of the response modes around the critical layer. A pleasing link is made to the classical laminar inviscid theory, whereby the essential mechanism underlying the hairpin vortex is captured by two obliquely interacting Kelvin–Stuart (cat’s eye) vortices. Evidence for the theory is presented based on comparison with observations of Structure in turbulent flow reported in the experimental and numerical simulation literature and with exact solutions reported in the transitional literature.