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  • 1
    Publication Date: 2017-01-05
    Description: Author Posting. © American Geophysical Union, 2010. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 115 (2010): C08003, doi:10.1029/2009JC005702.
    Description: The estuarine boundary layer affected by a horizontal density gradient exhibits temporal evolution over a tidal cycle, in a manner similar to the diurnal cycle of the ocean surface mixed layer. A large eddy simulation (LES) model is developed to investigate the physics controlling the growth of the boundary layer during the flood tide and restratification during the ebb tide. Turbulent kinetic energy, momentum and salt fluxes, bottom stress, and energy dissipation rates calculated from the LES model all show a strong flood-ebb asymmetry. Analysis of the turbulent kinetic energy (TKE) budget shows a primary balance between shear production and dissipation in the well-mixed boundary layer over the tidal cycle. However, TKE transport term is found to be important across the edge of the boundary layer during the flood tide so turbulent energy generated in the bottom boundary layer can be transferred to the stratified pycnocline region. Tidal straining leads to a small and weakly convective region inside the boundary layer during the flood tide but the strain-induced buoyancy flux does not make a significant contribution to the turbulence generation. Additional LES runs are conducted by switching off the baroclinic pressure gradient term in the momentum equation and the tidal straining term in the salinity equation to show that the baroclinic pressure gradient is the main mechanism responsible for generating the flood-ebb mixing asymmetry.
    Description: This work is supported by grants OCE-0451699 (M.L.), OCE-0452380 (U.P. and S.R.), and OCE-0451740 (W.R.G.) from the National Science Foundation.
    Keywords: Estuarine mixing ; Large Eddy Simulations ; Tidal straining
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
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  • 2
    Publication Date: 2019-07-12
    Description: Multiphase turbulent flows are encountered in many practical applications including turbine engines or natural phenomena involving particle dispersion. Numerical computations of multiphase turbulent flows are important because they provide a cheaper alternative to performing experiments during an engine design process or because they can provide predictions of pollutant dispersion, etc. Two-phase flows contain millions and sometimes billions of particles. For flows with volumetrically dilute particle loading, the most accurate method of numerically simulating the flow is based on direct numerical simulation (DNS) of the governing equations in which all scales of the flow including the small scales that are responsible for the overwhelming amount of dissipation are resolved. DNS, however, requires high computational cost and cannot be used in engineering design applications where iterations among several design conditions are necessary. Because of high computational cost, numerical simulations of such flows cannot track all these drops. The objective of this work is to quantify the influence of the number of computational drops and grid spacing on the accuracy of predicted flow statistics, and to possibly identify the minimum number, or, if not possible, the optimal number of computational drops that provide minimal error in flow prediction. For this purpose, several Large Eddy Simulation (LES) of a mixing layer with evaporating drops have been performed by using coarse, medium, and fine grid spacings and computational drops, rather than physical drops. To define computational drops, an integer NR is introduced that represents the ratio of the number of existing physical drops to the desired number of computational drops; for example, if NR=8, this means that a computational drop represents 8 physical drops in the flow field. The desired number of computational drops is determined by the available computational resources; the larger NR is, the less computationally intensive is the simulation. A set of first order and second order flow statistics, and of drop statistics are extracted from LES predictions and are compared to results obtained by filtering a DNS database. First order statistics such as Favre averaged stream-wise velocity, Favre averaged vapor mass fraction, and the drop stream-wise velocity, are predicted accurately independent of the number of computational drops and grid spacing. Second order flow statistics depend both on the number of computational drops and on grid spacing. The scalar variance and turbulent vapor flux are predicted accurately by the fine mesh LES only when NR is less than 32, and by the coarse mesh LES reasonably accurately for all NR values. This is attributed to the fact that when the grid spacing is coarsened, the number of drops in a computational cell must not be significantly lower than that in the DNS.
    Keywords: Man/System Technology and Life Support
    Type: NPO-48202 , NASA Tech Briefs, August 2013; 23-24
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  • 3
    Publication Date: 2019-07-12
    Description: High-fidelity models of plume-regolith interaction are difficult to develop because of the widely disparate flow conditions that exist in this process. The gas in the core of a rocket plume can often be modeled as a time-dependent, high-temperature, turbulent, reacting continuum flow. However, due to the vacuum conditions on the lunar surface, the mean molecular path in the outer parts of the plume is too long for the continuum assumption to remain valid. Molecular methods are better suited to model this region of the flow. Finally, granular and multiphase flow models must be employed to describe the dust and debris that are displaced from the surface, as well as how a crater is formed in the regolith. At present, standard commercial CFD (computational fluid dynamics) software is not capable of coupling each of these flow regimes to provide an accurate representation of this flow process, necessitating the development of custom software. This software solves the fluid-flow-governing equations in an Eulerian framework, coupled with the particle transport equations that are solved in a Lagrangian framework. It uses a fourth-order explicit Runge-Kutta scheme for temporal integration, an eighth-order central finite differencing scheme for spatial discretization. The non-linear terms in the governing equations are recast in cubic skew symmetric form to reduce aliasing error. The second derivative viscous terms are computed using eighth-order narrow stencils that provide better diffusion for the highest resolved wave numbers. A fourth-order Lagrange interpolation procedure is used to obtain gas-phase variable values at the particle locations.
    Keywords: Man/System Technology and Life Support
    Type: NPO-47694 , NASA Tech Briefs, August 2012; 25-26
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