Extended Self Similarity of Passive Scalar in Rayleigh-Bénard Convection Flow Based on Wavelet Transform

FU Qiang; XIA Ke-qing

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Article Navigation > Applied Mathematics and Mechanics > 2002 > 23(7): 715-721

FU Qiang, XIA Ke-qing. Extended Self Similarity of Passive Scalar in Rayleigh-Bénard Convection Flow Based on Wavelet Transform[J]. Applied Mathematics and Mechanics, 2002, 23(7): 715-721.

Citation:

FU Qiang, XIA Ke-qing. Extended Self Similarity of Passive Scalar in Rayleigh-Bénard Convection Flow Based on Wavelet Transform[J]. Applied Mathematics and Mechanics, 2002, 23(7): 715-721.

Citation:

FU Qiang, XIA Ke-qing. Extended Self Similarity of Passive Scalar in Rayleigh-Bénard Convection Flow Based on Wavelet Transform[J]. Applied Mathematics and Mechanics, 2002, 23(7): 715-721.

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Extended Self Similarity of Passive Scalar in Rayleigh-Bénard Convection Flow Based on Wavelet Transform

FU Qiang^1,2,
XIA Ke-qing²

1.
College of Physics, Meteorology Institute of Science and Engineering University of PLA, Nanjing 211101, P R China;
2.
Department of Physcis, Chinese University of Hong Kong, Shatian, Hong Kong, P R China

Received Date: 2001-12-25
Rev Recd Date: 2002-04-15
Publish Date: 2002-07-15

Abstract

Abstract

Wavetet transform was used to analyze the scaling rule of temperature data (passive scalar) in Rayleigh-B nard convection flow from two aspects. The first one was to utilize the method of extended self similarity, presented first by Benzi et al, to study the scaling exponent of temperature data. The obtained results show that the inertial range is much wider than that one determined directly from the conventional structure function, and find the obtained scaling exponent agrees well with the one obtained from the temperature data in an experiment of wind tunnel. The second one was that,by extending the formula which was proposed by A. Armeodo et al for extracting the scaling exponent (q) of velocity data to temperature data, a newly defined formula which is also based to wavelet transform, and can determine the scaling exponent ξ(q) of temperature data was proposed. The obtained results demonstrate that by using the method which is named as WTNN (wavelet transfrom maximum modulus) ξ(q) correctly can be extracted.
- Rayleigh-B nard convection,
- wavelet transform,
- extended self similarity,
- temperaturedata Rayleigh-B nard convection

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References(17)

References

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