Chinese Journal of Theoretical and Applied Mechani ›› 2016, Vol. 48 ›› Issue (6): 1319-1325.DOI: 10.6052/0459-1879-16-180

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AN IMPROVED METHOD FOR INITIALIZING HOMOGENEOUS ISOTROPIC TURBULENT FLOWS

Qin Zecong1,2, Fang Le1   

  1. 1. Sino-French Engineer School, Beihang University, Beijing 100191, China;
    2. LMFA, CNRS, Ecole Centrale de Lyon-Université de Lyon, Ecully 69130, France
  • Received:2016-07-01 Revised:2016-09-04 Online:2016-11-15 Published:2016-11-25
  • Contact: 10.6052/0459-1879-16-180

Abstract:

Homogeneous isotropic turbulence (HIT) is one of the simplest ideal turbulence states, and is also one of the most important subjects in basic turbulence theory researches. HIT fields are usually initialized in the spectrum space via the method proposed by Rogallo, and then transformed in physical space. The current paper points out that initial fields thus generated are anisotropic in axis directions of their computational domain, which can be reflected in structure functions and in possibility density distribution of velocity components. Even though such anisotropy will disappear after an average operation of a large number of initial field samples, the anisotropy fluctuation between samples is considerately big, which is not favorable for the establishment of an HIT. Basing on this existing methodology, we then proposed an improved Rogallo method, named the modulus-averaging method, which firstly conducts the Rogallo method in all the 3 axis directions, then carries out a modulus-averaging operation, and finally control the modulus via a given spectrum function. This method can keep the initial filed spectrum and, reduce the anisotropy fluctuation of each single field to generate "more isotropic" initial fields. Statistically, this new method can lower the relative standard deviations of structure functions and velocity possibility density distribution by about 10%.

Key words:

homogeneous isotropic turbulence|rogallo initialization method|structure function|possibility density distribution

CLC Number: