Summary
This paper focuses on a method proposed for diagnosing the presence of chaotic behaviour in physical systems directly from experimental time series. The procedure relies on the concept of short-term predictability of chaotic motions. From a statistical point of view, it is completely non-parametric and works whatever the distribution function of the data points may be. The method is robust to observational noise, and can distinguish merely linear stochastic processes,e.g., fractional Brownian motion, from truly non-linear deterministic systems. The capability of the method has been evaluated by applying it to intermittent gas-liquid flows in a horizontal pipe. A weak sign of deterministic chaos has been diagnosed in plug and slug flow regimes. Our analysis fully confirms the Ruelle-Takens view about the complexity in hydrodynamical systems. However, the weak sign of chaos is in contrast with the Lorenz type systems (strong chaos) and supports the idea of Kolmogorov about irregular motion in hydrodynamical systems.
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Drahoš, J., Punčochář, M., Nino, E. et al. Finding chaos in experimental time series: The case of two-phase flow. Il Nuovo Cimento B 110, 1415–1428 (1995). https://doi.org/10.1007/BF02849840
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DOI: https://doi.org/10.1007/BF02849840