7 research outputs found

    An early warning system for multivariate time series with sparse and non-uniform sampling

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    In this paper we propose a new early warning test statistic, the ratio of deviations (RoD), which is defined to be the root mean squared of successive differences divided by the standard deviation. We show that RoD and autocorrelation are asymptotically related, and this relationship motivates the use of RoD to predict Hopf bifurcations in multivariate systems before they occur. We validate the use of RoD on synthetic data in the novel situation where the data is sparse and non-uniformly sampled. Additionally, we adapt the method to be used on high-frequency time series by sampling, and demonstrate the proficiency of RoD as a classifier.Comment: 14 pages, 8 figure

    Application of the Turbulent Potential Model to Unsteady Flows and Three-Dimensional Boundary Layers

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    The turbulent potential model is a Reynolds-averaged (RANS) turbulence model that is theoretically capable of capturing nonequilibrium turbulent flows at a computational cost and complexity comparable to two-equation models. The ability of the turbulent potential model to predict nonequilibrium turbulent flows accurately is evaluated in this work. The flow in a spanwise-driven channel flow and over a swept bump are used to evaluate the turbulent potential model's ability to predict complex three-dimensional boundary layers. Results of turbulent vortex shedding behind a triangular and a square cylinder are also presented in order to evaluate the model's ability to predict unsteady flows. Early indications suggest that models of this type may be capable of significantly enhancing current numerical predictions of turbomachinery components at little extra computational cost or additional code complexity

    Multibody Interactions in Coarse-Graining Schemes for Extended Systems

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