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PRELIMINARY RESULTS OF LES SIMULATIONS OF SELF-SIMILAR VARIABLE ACCELERATION RT MIXING FLOWS D L YOUNGS AWE ALDERMASTON, UK A LLOR CEA BRUYRES-LE-CHTEL, FRANCE The importance of self-similar variable acceleration RT flows (SSVARTs)


  1. PRELIMINARY RESULTS OF LES SIMULATIONS OF SELF-SIMILAR VARIABLE ACCELERATION RT MIXING FLOWS D L YOUNGS AWE ALDERMASTON, UK A LLOR CEA BRUYÈRES-LE-CHÂTEL, FRANCE

  2. The importance of self-similar variable acceleration RT flows (SSVARTs) for the design and calibration of turbulent mixing models is shown in the presentation by Antoine Llor at this workshop. Because experimental results on SSVARTs are not, and will probably not be available in the near future, we are currently investigating such flows by means of LES. In these incompressible flows the acceleration has the form g = kt n and for self-similar mixing the mixing zone width grows in t . proportion to n+2 Preliminary results, using low-resolution LES are given for n = 0, 1 and -1, using the TURMOIL3D code. Results are compared with simple theoretical models.

  3. THE TEST PROBLEM This is based on the test problem proposed by Guy Dimonte (see presentation at this workshop). fluid 1 15H ρ = ρ 1 = 3 32 fluid 2 g 17H ρ = ρ 2 = 1 32 H Computational domain : H x H x 2H Zoning : 128 x 128 x 256 Dimension : H =1 Acceleration : (a) g = 2 (b) g = t (c) g = 9/(4t) Run to t = 4.5, when for each case ( ) 2 g dt = 40.5 ∫ Compressible calculation with Mach number < 0.2

  4. The major calculational problem is the treatment of variable g within a compressible calculation. For incompressible flow, the pressure distribution adjusts at each instant . = div u 0 of time to maintain If no mixing occurs this implies hydrostatic equilibrium. ∂ p = ρ g ∂ z In the compressible simulations an appropriate pressure gradient is maintained by adding an internal energy source. Initially adiabatic hydrostatic equilibrium (uniform entropy/neutral stability within each fluid) is assumed:- ∂ p 0 = ρ g 0 0 ∂ z ρ γ = p k , in each region 0 0 3 just above the interface   ρ 0 =  1 just below the interface  � γ = 5 3 for both fluids

  5. g If is the value of g for the n-th time step, at the start of the time step n+1 2 the internal energy is scaled:- g n+1 ε ε ′ = . 2 g n- 1 2 This maintains hydrostatic equilibrium outside the mixing zone and uniform entropy within each fluid. The acceleration history needs to be modified slightly to give finite non- zero g at t = 0:- { } max 0.01, t case (b) g = { } ( ) case (c) g = min 50, 9/ 4t The initial interface pressure is chosen high enough to ensure that the Mach no. of the flow remains small (M<0.2) at all times and also high enough to give small (<4%) variation in the initial density of each region.

  6. THE INITIAL PERTURBATION RT experiments with constant g give bubble penetration ρ − ρ 2 = α 1 2 α h gt , with ~ 0.05 to 0.06 1 ρ + ρ 1 2 TURMOIL3D calculations with short wavelength initial perturbations (growth purely by α ~ 0.03. mode coupling) give ∝ Need to assume long wavelength initial perturbations with amplitude α ~ 0.05. wavelength (as proposed by Inogamov [1]) to give self-similar growth with ( ) = ξ ξ + ξ x,y Perturbation used S L ξ S ∆ ∆ 4 x to 8 x : wavelengths s.d = ∆ 0.02 x ξ L : power spectrum P(k) 1   2 ∞     ( ) σ λ = = ε λ P k dk ∫   π λ   2   �  ( ) P k 1 k 3 ⇒ ∞ ε = 0.0005 4 x to H ∆ wavelengths in the range 2

  7. RESULTS SHOWN , f f : volume fractions of fluids 1 and 2 1 2 , f f : plane averaged values 1 2 f f dz W = ∫ integral mix width 1 2 h 1 f 1 : bubble penetration - measured to point where = 0.99. 1 = h 3.3W Approximation used here : f f dz ∫ 1 2 θ = , molecular mixing fraction f .f dz ∫ 1 2 D KE dissipated = P KE production ρ − ρ ( ) 2 S = 1 2 g dt ∫ ρ + ρ 1 2 Fig 1 : initial long wavelength perturbation Fig 2 : isosurfaces for the case g = k f 1 Fig 3 : profiles of h 1 Fig 4 : plots of θ Fig 5 : plots of Fig 6 : plots of D/P

  8. Figure 1 = 0.005, initial perturbation x 200

  9. Figure2: Isosurfaces (f 1 = 0.99) for g =k t = 0.9 t = 3.5

  10. � COMPARISON OF RESULTS WITH SIMPLE MODELS (A) The Simplest Model Bubbles of radius R have a limiting velocity If it is assumed that ~ AgR . R ~ h , then 1 = h c Agh 1 1 2   t ( )   = α ′ ′ α ie h A g t dt = S . . .(1) ∫   1   � o  Figure 5 shows plots of The slopes of the curves (for the range h vs S. 1 ε = 0.0005 h H = 0.25 to 0.75) give; for 1 α n = 0 , = 0.0464 α n = 1 , = 0.0415 α n = -1 , = 0.0559 α The model works surprisingly well, but there is some variation of with n:- α = 0.89 1 α 0 α = -1 1.20 α 0

  11. ✁ ✁ ✁ (B) A Buoyancy - Drag Model A model of this type, based on a modified form of Layzer’s equation for a bubble rising in a cylindrical tube, was used by Hansom et al [2]. 2   C h     . . . (2) = − D 1 h Ag 1 h 1 acceleration = buoyancy - drag α = 0.05. D = α C 4.5 For constant g, gives Then if is defined as in equation (1):- α = 0.97 1 α 0 α = -1 1.11 α 0 α This is closer to the TURMOIL3D results than taking independent of n but the change is not large enough. β <1 Dimonte and Schneider [3] include a factor in front of the Ag term in equation (2). This improves agreement with the 3D simulations.

  12. ✆ ✆ ☎ ☎ ☎ ✄ ✂ ✞ ✝ (C) An Energy Balance Model This is version of the model proposed by Ramshaw [4], but with different settings for the model coefficients. K = 1   ρ + ρ 2   h V Let = kinetic energy within the mixing layer.   2 1 1 2 P = KE production rate (loss of potential energy) D = dissipation rate Then the model equations used are K = P - D   ρ − ρ P = c   g h h   1 1 1 1 2 D = c 1   3 ρ + ρ   V   2 2 1 2 = h c V 1 3 The coefficient depends on the shape of the volume fraction profile. For a linear c 1 1 = c 1 3. 1 = distribution For the TURMOIL3D profiles (figure 4) and this is the c 0.30, value used here. α = 0.05 and D P = 0.4 If for constant g we assume, (figure 7) then 2 = c 1.4055 3 = c 1.0541

  13. ✟ ✡ ✟ ✟ ✠ ✠ ✠ K = P-D The equation gives 2   h + c c     1 = h c c Ag - 2 2 3 1 1 3 2c h 3 1 2   h   3 Ag - 7 = 1   1 6 h . . . (3) 1 This has the same form as the buoyancy - drag model (2). The coefficient in front of the Ag term is less than unity as in Dimonte and Schneider [3]. This choice of the coefficients gives α = 1 0.91 α 0 α = 1.43 -1 α 0 also D/P = 0.40 assumed for n = 0 D/P = 0.36 for n = 1 D/P = 0.57 for n = -1 α α agrees with the 3D simulations 1 0 α α appears to be somewhat too high. However, the variation of D/P -1 0 with n (see fig. 6) is represented very well.

  14. FUTURE PLANS · Values of n outside the range [-1, 1] · Higher resolution TURMOIL3D calculations · Use of the SSVARTs results to differentiate between various types of RANS models. REFERENCES 1. N A Inogamov et al, Proceedings of the 3rd IWPCTM, Royaumont (1991) 2. J C V Hansom et al, Laser and Particle Beams, Vol 8, p 51 (1990) 3. G Dimonte and M Schneider, Phys Rev E54, p 3740 (1996) 4. J D Ramshaw, Phys Rev E58, p 5834 (1998)

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