1,881 research outputs found

    Complex Networks Unveiling Spatial Patterns in Turbulence

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    Numerical and experimental turbulence simulations are nowadays reaching the size of the so-called big data, thus requiring refined investigative tools for appropriate statistical analyses and data mining. We present a new approach based on the complex network theory, offering a powerful framework to explore complex systems with a huge number of interacting elements. Although interest on complex networks has been increasing in the last years, few recent studies have been applied to turbulence. We propose an investigation starting from a two-point correlation for the kinetic energy of a forced isotropic field numerically solved. Among all the metrics analyzed, the degree centrality is the most significant, suggesting the formation of spatial patterns which coherently move with similar vorticity over the large eddy turnover time scale. Pattern size can be quantified through a newly-introduced parameter (i.e., average physical distance) and varies from small to intermediate scales. The network analysis allows a systematic identification of different spatial regions, providing new insights into the spatial characterization of turbulent flows. Based on present findings, the application to highly inhomogeneous flows seems promising and deserves additional future investigation.Comment: 12 pages, 7 figures, 3 table

    Spatial characterization of turbulent channel flow via complex networks

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    A network-based analysis of a turbulent channel flow numerically solved at Reτ=180Re_\tau=180 is proposed as an innovative perspective for the spatial characterization of the flow field. Two spatial networks corresponding to the streamwise and wall-normal velocity components are built, where nodes represent portions of volume of the physical domain. For each network, links are active if the correlation coefficient of the corresponding velocity component between pairs of nodes is sufficiently high, thus unveiling the strongest kinematic relations. Several network measures are studied in order to explore the interrelations between nodes and their neighbors. Specifically, long-range links are localized between near-wall regions and associated with the temporal persistence of coherent patterns, namely high and low speed streaks. Furthermore, long-range links play a crucial role as intermediary for the kinematic information flow, as emerges from the analysis of indirect connections between nodes. The proposed approach provides a framework to investigate spatial structures of the turbulent dynamics, showing the full potential of complex networks. Although the network analysis is based on the two-point correlation, it is able to advance the level of information, by exploiting the texture created by active links in all directions. Based on the observed findings, the current approach can pave the way for an enhanced spatial interpretation of the turbulence dynamics

    Chaotic versus stochastic behavior in active-dissipative nonlinear systems

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    We study the dynamical state of the one-dimensional noisy generalized Kuramoto-Sivashinsky (gKS) equation by making use of time-series techniques based on symbolic dynamics and complex networks. We focus on analyzing temporal signals of global measure in the spatiotemporal patterns as the dispersion parameter of the gKS equation and the strength of the noise are varied, observing that a rich variety of different regimes, from high-dimensional chaos to pure stochastic behavior, emerge. Permutation entropy, permutation spectrum, and network entropy allow us to fully classify the dynamical state exposed to additive noise

    Inside outsourcing: A grounded theory of relationship formation within a nascent service system

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    The theory of relationship formation developed in this study tells a coherent story about the relational work of service initiation in technology outsourcing. The study is focused on the contractually defined period of time at the beginning of outsourcing service delivery. As with a play-within-a-play, this work goes on primarily behind the scenes, away from the concurrent task of launching the inter-firm relationship between the client and the provider that will extend for the term of the full contract. This grounded theory study was completed over an eight-month period. The findings are grounded in interviews with 25 individuals who were actively involved in the work of service initiation. Additionally, data sources included extensive observation and access to documents and other artifacts. Data analysis was completed with the analytic processes of dimensional and situational analysis. The situational analysis describes five continuously shifting aspects of the situation that create the context, or supporting structure, for relationship formation. The dimensional analysis builds from the situational analysis to describe four deeply interrelated dimensions: (1) Helping, (2) Veiling / unVeiling, (3) Having Expectation, and (4) Responding to Turbulence. The study then presents a conceptual model of a grounded theory of relationship. It is through the enactment of this total model that relationship formation can be recognized as a vehicle for accomplishing work. An understanding that relationship formation depends on a way of recognizing and honoring the power of relationships and the role they play in supporting the everyday tasks of service initiation emerged from this work. As a result, this study does not strive to define relationship as one thing or even a group of things. Instead, it proposes a conceptual model through which relationships are formed and can be recognized as such. The electronic version of this dissertation is accessible at the OhioLINK ETD Center, https://etd.ohiolink.edu

    Topological transformations of speckles

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    Deterministic control of coherent random light is highly important for information transmission through complex media. However, only a few simple speckle transformations can be achieved through diffusers without prior characterization. As recently shown, spiral wavefront modulation of the impinging beam allows permuting intensity maxima and intrinsic ±1\pm 1-charged optical vortices. Here, we study this cyclic-group algebra when combining spiral phase transforms of charge nn, with D3D_3- and D4D_4-point-group symmetry star-like amplitude modulations. This combination allows statistical strengthening of permutations and controlling the period to be 3 and 4, respectively. Phase saddle-points are shown to complete the cycle. These results offer new tools to manipulate critical points in speckles.Comment: 14 pages, 10 figures, 4 table
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