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  • 1
    Electronic Resource
    Electronic Resource
    Shear induced diffusive mixing in simulations of dense Couette flow of rough, inelastic hard spheres (1998)
    College Park, Md. : American Institute of Physics (AIP)
    The Journal of Chemical Physics 109 (1998), S. 4487-4491 
    Details
    ISSN: 1089-7690
    Source: AIP Digital Archive
    Topics: Physics , Chemistry and Pharmacology
    Notes: Large-scale numerical simulations of a system of inelastic, rough, hard spheres of volume fraction φs=0.565, which are initially distributed randomly in a Couette geometry, show clear evidence of the movement of the particles in directions transverse to the bulk motion. This behavior of the aforementioned system, which has been considered as a model for a granular fluid, is consistent with recent experimental observations [Hsiau and Hunt, J. Fluid Mech. 251, 299 (1993)]. Based on the results obtained, there are indications that a bounded rapid granular flow could be a diffusive system at volume fractions even higher than 0.56. This finding contradicts earlier computer experiments [Campbell, J. Fluid Mech. 348, 85 (1997)] which found a rapidly flowing granular material is a diffusive system except at large solids concentrations (i.e., φs〉0.56). © 1998 American Institute of Physics.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1063/1.477076
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  • 2
    Electronic Resource
    Electronic Resource
    Bond-orientational order in sheared dense flows of inelastic hard spheres (1998)
    Woodbury, NY : American Institute of Physics (AIP)
    Applied Physics Letters 73 (1998), S. 450-452 
    Details
    ISSN: 1077-3118
    Source: AIP Digital Archive
    Topics: Physics
    Notes: Three-dimensional bond-orientational order is studied using computer simulations with 4296 hard, monodisperse inelastic spheres flowing in a Couette geometry at a high shear rate. At an average volume fraction close to 0.6, a state with extended correlations in the orientations of particle clusters starts to develop for rough particles after sufficiently long run times. However, no clear evidence of crystallization is found in the system. Further tests of a sheared system comprised of smooth, inelastic spheres reveal crystallization consistent with the previous experimental observations. © 1998 American Institute of Physics.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1063/1.121896
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  • 3
    Electronic Resource
    Electronic Resource
    Some qualitative features of the Couette flow of monodisperse, smooth, inelastic spherical particles (1997)
    Woodbury, NY : American Institute of Physics (AIP)
    Applied Physics Letters 71 (1997), S. 3790-3792 
    Details
    ISSN: 1077-3118
    Source: AIP Digital Archive
    Topics: Physics
    Notes: Computer simulations have been performed to examine the occurrence of power-law correlations for the stresses exerted on the confining walls by the particles in the three dimensional Couette flow of hard, smooth, dissipative spherical particles of uniform size. At high particle concentrations, the wavelet analysis of the wall shear stress has revealed the existence of anomalous, long-ranged temporal correlations. Based on the results obtained, there are indications that the dense Couette flow of monodisperse, smooth, inelastic, spherical particles is a system which may be characterized by continuous distributions of the physical measures of its particles, such as size. © 1997 American Institute of Physics.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1063/1.120507
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  • 4
    Electronic Resource
    Electronic Resource
    Application of neural networks to mass-transfer predictions in a fast fluidized bed of fine solids (1997)
    Hoboken, NJ : Wiley-Blackwell
    AIChE Journal 43 (1997), S. 1684-1690 
    Details
    ISSN: 0001-1541
    Keywords: Chemistry ; Chemical Engineering
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology , Process Engineering, Biotechnology, Nutrition Technology
    Notes: In this study back-propagation, feed-forward neural networks are applied to estimate mass-transfer parameters in fast fluidized beds of fine solids. These networks are trained to predict mass-transfer rates using measurements of the sublimation rate of coarse naphthalene balls in fast fluidized beds of fine glass beads at several solid-to-gas mass flow rates within the relevant superficial gas-velocity range. When tested to predict the effective diffusivities from a coarse particle to the bulk of the fast bed of fine solids, trained neural networks calculated the Sherwood number with high accuracy. It is demonstrated that back-propagation, feed-forward neural networks provide a more accurate correlation for the mass-transfer coefficient compared to those obtained by the currently used heuristic models.
    Additional Material: 5 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/aic.690430705
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