MULTIFRACTAL CHARACTERISTICS OF AXISYMMETRIC JET TURBULENCE INTENSITY FROM RANS NUMERICAL SIMULATION

被引:2
作者
Seo, Yongwon [1 ]
Ko, Haeng Sik [2 ]
Son, Sangyoung [3 ]
机构
[1] Yeungnam Univ, Dept Civil Engn, Gyongsan 38541, South Korea
[2] Jeju Natl Univ, Dept Ocean Syst Engn, Jeju 63243, South Korea
[3] Korea Univ, Sch Civil Environm & Architectural Engn, Seoul 02841, South Korea
基金
新加坡国家研究基金会;
关键词
Multifractal; Turbulence Intensity; Box-Count Method; Reynolds-Averaged Navier-Stokes Equations; k-epsilon Model; k-omega Model; LARGE-EDDY SIMULATION; FLOW DISTRIBUTION; NOZZLE GEOMETRY; MODEL; NETWORKS; FIELD;
D O I
10.1142/S0218348X18500081
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
A turbulent jet bears diverse physical characteristics that have been unveiled yet. Of particular interest is to analyze the turbulent intensity, which has been a key factor to assess and determine turbulent jet performance since diffusive and mixing conditions are largely dependent on it. Multifractal measures are useful in terms of identifying characteristics of a physical quantity distributed over a spatial domain. This study examines the multifractal exponents of jet turbulence intensities obtained through numerical simulation. We acquired the turbulence intensities from numerical jet discharge experiments, where two types of nozzle geometry were tested based on a Reynolds-Averaged Navier-Stokes (RANS) equations. The k-epsilon model and k-omega model were used for turbulence closure models. The results showed that the RANS model successfully regenerates transversal velocity profile, which is almost identical to an analytical solution. The RANS model also shows the decay of turbulence intensity in the longitudinal direction but it depends on the outfall nozzle lengths. The result indicates the existence of a common multifractal spectrum for turbulence intensity obtained from numerical simulation. Although the transverse velocity profiles are similar for two different turbulence models, the minimum Lipschitz-Holder exponent (alpha(min)) and entropy dimension (alpha(1)) are different. These results suggest that the multifractal exponents capture the difference in turbulence structures of hierarchical turbulence intensities produced by different turbulence models.
引用
收藏
页数:14
相关论文
共 36 条
[21]   Influence of jet exit conditions on the passive scaler field of an axisymmetric free jet [J].
Mi, J ;
Nobes, DS ;
Nathan, GJ .
JOURNAL OF FLUID MECHANICS, 2001, 432 :91-125
[22]   MULTIFRACTALITY OF FLOW DISTRIBUTION IN THE RIVER-NETWORK MODEL OF SCHEIDEGGER [J].
NAGATANI, T .
PHYSICAL REVIEW E, 1993, 47 (01) :63-66
[23]  
Parisi G., 1985, Turbulence and Predictability in Geophysical Fluid Dynamics and Climate Dynamics, P84
[24]  
Pope S. B., 2000, TURBULENT FLOWS, Vxxxiv
[25]  
Rodi W, 1997, J WIND ENG IND AEROD, V71, P55
[26]   Multifractal characteristics of the jet turbulent intensity depending on the outfall nozzle geometry [J].
Seo, Yongwon ;
Lyu, Siwan .
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2016, 30 (02) :653-664
[27]   Multifractal properties of the peak flow distribution on stochastic drainage networks [J].
Seo, Yongwon ;
Schmidt, Arthur R. ;
Kang, Boosik .
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2014, 28 (05) :1157-1165
[28]   A NEW KAPPA-EPSILON EDDY VISCOSITY MODEL FOR HIGH REYNOLDS-NUMBER TURBULENT FLOWS [J].
SHIH, TH ;
LIOU, WW ;
SHABBIR, A ;
YANG, ZG ;
ZHU, J .
COMPUTERS & FLUIDS, 1995, 24 (03) :227-238
[29]   THE FRACTAL NATURE OF RIVER NETWORKS [J].
TARBOTON, DG ;
BRAS, RL ;
RODRIGUEZ-ITURBE, I .
WATER RESOURCES RESEARCH, 1988, 24 (08) :1317-1322
[30]  
Tchiguirinskaia I, 2000, STOCH ENV RES RISK A, V14, P8