Quantitative Analysis of Two-Phase Flow Time Series Based on Optimal Orbit Reconstruction and Point Correlation Dimension
The nonlinear time series analysis of two-phase flow is difficult, and the analysis sometimes results subjectively. Using artificially generated quasiperiodic data and submerged nozzle pressure fluctuation, we showed that applying an optimal delay time reconstruction method and a point correlation d...
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| Published in | Nihon Kikai Gakkai rombunshuu. B hen Vol. 72; no. 715; pp. 590 - 597 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | Japanese |
| Published |
The Japan Society of Mechanical Engineers
2006
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| Subjects | |
| Online Access | Get full text |
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| Abstract | The nonlinear time series analysis of two-phase flow is difficult, and the analysis sometimes results subjectively. Using artificially generated quasiperiodic data and submerged nozzle pressure fluctuation, we showed that applying an optimal delay time reconstruction method and a point correlation dimension method together greatly improved the reliability of the analysis. In this paper, we analyze real two-phase flows time series : differential pressure and void fraction of slug and bubbly flow in a vertical pipe. The comparisons of estimated results and their statistical test results demonstrate the high reliability of the proposed analysis method. |
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| AbstractList | The nonlinear time series analysis of two-phase flow is difficult, and the analysis sometimes results subjectively. Using artificially generated quasiperiodic data and submerged nozzle pressure fluctuation, we showed that applying an optimal delay time reconstruction method and a point correlation dimension method together greatly improved the reliability of the analysis. In this paper, we analyze real two-phase flows time series : differential pressure and void fraction of slug and bubbly flow in a vertical pipe. The comparisons of estimated results and their statistical test results demonstrate the high reliability of the proposed analysis method. |
| Author | MINATO, Akihiko SUZUKI, Akio MISAWA, Masaki |
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| References | (9) Rosenstein, M.T. et al., Reconstruction expansion as a geometry-based framework for choosing proper delay times, Physica D, Vol. 73, No. 1-2, (1994), pp. 82-98. (6) Yano T. et al., Nonlinear Hydrodynamics of Three-Phase Reactors, Journal of the Society of Chemical Engineers Japan, Vol. 25, No. 4, (1999), pp. 530-534 (5) Wang, S.F. et al., Nonlinear analysis on fluctuation feature of two-phase flow through a T-junction, International Journal of Heat and Mass Transfer, Vol. 46, No. 9, (2003), pp. 1519-1528 (2) Kantz, H. and Schreiber, T., Nonlinear Time Series Analysis, (1997), Cambridge University Press. (8) National Institute of Advanced Industrial Science and Technology ed., Applied Complexity Engineering (in Japanese), (2005), p.73, Pleiades Publishing. (16) Misawa M. et al., Nonlinear Characteristics of Gas-Liquid Two-Phase Flow and Verification of Extended Two-Fluid Model, Proceedings of International Conference on Multiphase Flow, (2004), Paper No. 213. (7) Minato, A. et al., Report of Technology Development of Estimation Method for Complex Gas-Liquid Two-Phase Flow in Nuclear Reactors Project (in Japanese), (2004), The Institute of Applied Energy. (3) Johnsson, F. et al., Characterization of fluidization regimes by time-series analysis of pressure fluctuations, International Journal of Multiphase Flow, Vol. 26, No. 4, (2000), pp. 663-715. (10) Skinner, J.E. and Molnar, M., Event-related dimensional reductions in the primary auditory cortex of the conscious cat are revealed by new techniques for enhancing the non-linear dimensional algorithms, International Journal of Psychophysiology, Vol. 34, No. 1, (1999), pp. 21-35. (11) Veronig, A. et al., Determination of Fractal Dimensions of Solar Radio Burst, Astronomy & Astrophysics, Vol. 357, (2000), pp. 337-350. (15) Prasser, H.M. et al., A new electrode-mesh tomograph for gas-liquid flows, Flow Measurement and Instrumentation, Vo.9, No.2, (1998), pp.111-119 (4) Van den Bleek, C.M. et al., Application of chaos analysis to multiphase reactors, Chemical Engineering Science, Vol. 57, No. 22-23, (2002), pp. 4763-4778. (17) Judd, K., Estimating dimension from small samples, Physica D, Vol. 71, No. 4, (1994), pp. 421-429. (12) Suzuki, A., Improvement of reliability of two-phase flow characterization by point correlation dimension analysis and verification using submerged nozzle pressure fluctuation time series, Transactions of the Japan Society of Mechanical Engineers, Series B, Vol. 70, No. 692, (2004), pp. 896-903. (1) Aihara, K. ed., Fundamentals and Application of Chaos Time Series Analysis (in Japanese), (2000), Sangyo Tosho Publishing. (13) Grassberger, P. and Procaccia, I., Measuring the strangeness of strange attractors, Physica D, Vol. 9, No. 1-2, (1983), pp. 189-208. (14) Theiler, J., Efficient algorithm for estimating the correlation dimension from a set of discrete points, Physical Review A, Vol. 36, No. 9, (1987), pp. 4456-4462. |
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| SubjectTerms | Chaos Correlation Dimension Nonlinear Time Series Analysis Point Correlation Dimension Two-Phase Flow Void Fraction Wire-Mesh Sensor |
| Title | Quantitative Analysis of Two-Phase Flow Time Series Based on Optimal Orbit Reconstruction and Point Correlation Dimension |
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