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SIMULATION OF DUST DEVILS

SIMULATION OF DUST DEVILS. Zhaolin GU, PhD, Professor Xi’an Jiaotong University October , 2006, CCFD Forum , Tokyo University. Background. Atmospheric dust has important impacts on global and regional climates.

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SIMULATION OF DUST DEVILS

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  1. SIMULATION OF DUST DEVILS Zhaolin GU, PhD, Professor Xi’an Jiaotong University October , 2006, CCFD Forum , Tokyo University

  2. Background • Atmospheric dust has important impacts on global and regional climates. • Some specific convective wind systems in the convective boundary layer (CBL), such as, dust storms, dust devils etc., can carry dust into the atmosphere.

  3. Dust transportation in Northwestern arid area of China Dust storm Meso-scale meteorological process Dust devil Micro-scale meteorological process

  4. About dust storms – Some pictures The vision of Lanzhou Train Station at 16:00, April 10, 2004 The vision of Dunhuang Grottoes at 16:00, April 10, 2004 The vision of Xi’an City Wall, April 9, 2006 The destroyed window by the dust storm, April 9, 2006

  5. About dust storms – Meteorological aspects • A Mesoscale meteorological process, composed of strong convection cells • Height of dust front 300-400 m • Length of dust front around 100 km • second dust front 10-20 km • Horizontal velocity more than 20 ms-1 • Vertical velocity more than 15 ms-1 • Temperature increment (DT ) 4–8 K • Pressure depression (Dp) 2.0–3.5 hPa ΔT and Δp are departures from ambient values of temperature and pressure.

  6. About dust devils – Meteorological aspects • A special case of convective vortex occurring in the atmosphere boundary layer. • The most common, small-scale dust transmitting system. • Maybe the primary atmospheric dust-loading mechanism in non-storm seasons • Mixing grains in dust devils becoming tribo-electrified.

  7. Typical Observed Dust Devil Physical Characteristics • Diameter Tens to 141 m • Height 300–660 m • Horizontal velocity 5-20 ms-1 • Vertical velocity 3–15 ms-1 • Rotation sense Random • Temperature increment (ΔT ) 2–8 K • Pressure depression (Δp) 2.5–4.5 hPa ΔT and Δp are departures from ambient values of temperature and pressure.

  8. Inducement of dust devils—Background vorticity The Benard’s Convection in atmospheric boundary layer

  9. Inducement of dust devils—Background vorticity

  10. Inducement of dust devils— Surface roughness At h=5.2m and h=9.4m (V7and V31 in the figure), the value of tangential velocities at r=50m is different, where is far from the dust devil center and maybe the boundary of the dust devil. (P. C. Sinclair, 1973)

  11. Inducement of dust devils— Buoyancy • Heat radiation from the sun causing the rise of surface temperature • The temperature difference between the ground surface and the near-surface air parcels is over 20-30K at sunny mid-day in deserts (Li J. F. , Desert Climate, Meteorological Press, Beijing, 2002) • The temperature difference is related to the heat flux on the surface.

  12. Tool and methods for dust devil study • Field observation and test • Laboratory experiment, e.g. dry ice simulator in Arizona University • Numerical simulation gas-solid two-phase flow

  13. Numerical simulation C. B.Leovy, Nature, 424 ,2003 • Promise to be an important tool for interpreting laboratory and field observations of dust devils (C. B.Leovy, Nature, 424 ,2003) • Getting insights into the dynamics of boundary-layer vortices Two scale methods: convective boundary layer (CBL) scale simulation, and dust devil-scale simulation

  14. Dust devil-scale simulation method LES- Lagrangian discrete phase model (LDPM) model • LES for the turbulent flow • LDPM for the grain movement—one way coupling • Lifting of dust not actually appearing to be of major dynamical importance for the development of these vertical vortices ( P. C. Sinclair,J. Appl. Meteorol. 8,1969)

  15. LES Equations Continuity equation Momentum equation Energy equation

  16. Dynamic subgrid scheme Least-squares approach, Lilly (1992)

  17. Dust devil scale LES model—boundary conditions

  18. Involution of dust devils a) Weak vortex phase; b) Single cell phase; c) Transition phase of single cell to double cell; d) Double cell phase .

  19. Fine flow structure in the weak vortex phase The updraft vectors and contours of updraft velocity

  20. Fine flow structure in the single cell phase The updraft vectors and contours of updraft velocity

  21. Fine structure in transition phase of single cell to double cell The updraft vectors and contours of updraft velocity

  22. Fine flow structure in the double cell phase The updraft vectors and contours of updraft velocity

  23. Daughter vortices in the double cell phase

  24. Grain tracks in the mature phase flow 100mm 200mm 300mm

  25. Dust lifting patterns in a dust devil 1-track of fine dust grains; 2-track of medium grains; 3-track of large grains; 4-small vortices induced by the interaction of different sized grains; 5-general pattern of interactions.

  26. An illustration of the electric dust devil—Farrell et al. J. Geophys. Res., 109,2004

  27. Observed near-surface patterns of terrestrial dust devils

  28. Modeled dust devils and typical parameters

  29. Simulated near-surface patterns of dust devils Near-surface shapes of dust devils simplified by the periphery of the rotating velocity contour of their cores.

  30. Some problems in the numerical simulation • Grain size distribution • The influence of electrostatic field on the movement the positive-charged or negative-charged particles • The collision of particles resulting in charge neutralization and/or production, and then the particle movement

  31. Particle population balance model—an example

  32. Particle population balance model • A method connecting the microcosmic behaviors with the macroscopic token of dispersed phase • Description for different microcosmic behaviors in various process, such as crystal, growth, dissolution, breakage, aggregation, erosion, sinter and so on • Dealing with some process— formation or transformation of rain, snow and hail, aerosol, sand storm, dust devils

  33. Particle population balance equation (PPBE) n (L, us, t, x) particle number density function; usparticle velocity; L particle properties; X dimension ; Ttime ; S(L, us, x, t ) source tem, relating to the dispersed phase behaviors; F forces acting on the dispersed phase.

  34. Transformation Particle population balance equation (PPBE) Source term with no reaction

  35. Solution of the PPBE • Classification method (CM)—(N+1)-fluid model, one fluid corresponding to the gas phase and N fluids to the different size dispersed phase • Quadrature method of moment (QMOM) (McGraw,Aerosol. Sci. Technol., 27, 1997) • Direct Quadrature method of moment (DQMOM) (Marchisio et al., Chem. Eng. Sci., 58, 2003) • Monte Carlo Methods

  36. Prospect of CFD coupling with PPBE-1 • Extending the physical understanding of the dispersed phase behaviors and process • QMOM and DQMOM, based on the fundamental statistical concepts on the microscopic level, are the promise to solve the PPBE • Reformulation of the coalescence and breakage, consistent with QMOM and DQMOM • Improving the formulation of the turbulence effects, interfacial transfer fluxes • Improving the formation of the boundary conditions (inlet and outlet conditions, wall boundary)

  37. Prospect of dust simulation • The evaluation of dust flux at a level of dust devil on different surface • The possibility evaluation of occurring of dust devils in the region • The evaluation of regional dust flux from dust devils

  38. Thanks for your attention!

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