DOI QR코드

DOI QR Code

Statistical Characteristics of Fractal Dimension in Turbulent Prefixed Flame

난류 예혼합 화염에서의 프랙탈 차원의 통계적 특성

  • Lee, Dae-Hun (Dept. of Aerospace Engineering, Graduate School of Korea Advanced Institute of Science and Technology) ;
  • Gwon, Se-Jin
  • Published : 2002.01.01

Abstract

With the introduction of Fractal notation, various fields of engineering adopted fractal notation to express characteristics of geometry involved and one of the most frequently applied areas was turbulence. With research on turbulence regarding the surface as fractal geometry, attempts to analyze turbulent premised flame as fractal geometry also attracted attention as a tool for modeling, for the flame surface can be viewed as fractal geometry. Experiments focused on disclosure of flame characteristics by measuring fractal parameters were done by researchers. But robust principle or theory can't be extracted. Only reported modeling efforts using fractal dimension is flame speed model by Gouldin. This model gives good predictions of flame speed in unstrained case but not in highly strained flame condition. In this research, approaches regarding fractal dimension of flame as one representative value is pointed out as a reason for the absence of robust model. And as an extort to establish robust modeling, Presents methods treating fractal dimension as statistical variable. From this approach flame characteristics reported by experiments such as Da effect on flame structure can be seen quantitatively and shows possibility of flame modeling using fractal parameters with statistical method. From this result more quantitative model can be derived.

Keywords

References

  1. Richardson, L. E, 1922, 'Weather Prediction by Numerical Process,' Cambridge university press
  2. Mandelbrot, B. B., 1975 JFM, 72, 401 https://doi.org/10.1017/S0022112075003047
  3. Sreenivasan, K. R., 1991, Annu. Rev. Fluid, Meeh 23, 530-600
  4. Wu, C. K. and Law, C. K., 1984, 20th Symposium on Combustion. The Combustion lnst., pp.1941-1949
  5. Murayame, M. and Takeno, T., 1988, 22th Symposium on Combustion, The Combustion Inst., pp.551-559
  6. Takeno, T., Murayame, M., and Tanina, Y., 1990, Exp. In Fluids 10, 61-70 https://doi.org/10.1007/BF00215012
  7. Gouldin, F. C., Hilton, S. M. and Lamb, T., 1988, 22th Symposium on Combustion. The Combustion Inst., pp.541-550
  8. Yoshida, A., Ando, Y., Yanagisawa, T., and Tsuji, H., 1994, Comb. Sci. and Tech. V96, pp 121-134 https://doi.org/10.1080/00102209408935350
  9. Gouldin, F. C., 1987, Comb. and Flame 68. pp.249-266 https://doi.org/10.1016/0010-2180(87)90003-4
  10. Gouidin, F. C., Bray, K. N. c, Chen, 1. -Y., 1989, Comb. and Flame 77. pp.241-259 https://doi.org/10.1016/0010-2180(89)90132-6
  11. Goh, P. J., Shepherd, I. G. and Trinite, M., 1989, Comb. Sci. and Tech., V.63 pp.275-286 https://doi.org/10.1080/00102208908947132
  12. Peters, N.,1986, 21th Symposium on Combustion. The Combustion Inst., pp.1231-1250
  13. Smallwood, G. J., Gulder, O. L., Snelling, D. R., Deschamps, B. M. and Gokalp, I., 1995, Comb. and Flame V. 101 pp. 461--470 https://doi.org/10.1016/0010-2180(94)00226-I
  14. Mendenhall W., Wackerly, D. D. and Scheaffer, R. L., 1991, Mathematical Statistics with Applications, 4th Edit. Thomson Information / Publishing Group