A locally implicit improvement of the equilibrium Eulerian method

Ferry, Jim; Rani, Sarma L.; Balachandar, S.

doi:10.1016/s0301-9322(03)00064-8

Cited by 50 publications

(37 citation statements)

References 17 publications

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“…leading to the so-called equilibrium-Eulerian model developed by Ferry and Balachandar (2001), Ferry et al (2003) and Balachandar and Eaton (2010) for incompressible multiphase flows. Here α is a local correction coefficient inserted to avoid singularities (introduced by Ferry et al, 2003).…”

Section: Kinematic Decouplingmentioning

confidence: 99%

“…Here α is a local correction coefficient inserted to avoid singularities (introduced by Ferry et al, 2003). At the zeroth order we recover u j = u g + w j , where w j is the settling velocity defined in Eq.…”

Section: Kinematic Decouplingmentioning

confidence: 99%

“…In the FV method (Ferziger and Perić, 1996), the governing partial differential equations are integrated over a computational cell, and the Gauss theorem is applied to convert the volume integrals into surface integrals, involving surface fluxes. Reconstruction of scalar and vector fields (which are defined in the cell centroid) on the cell interface is a key step in the FV method, controlling both the accuracy and the stability properties of the numerical method.…”

Section: Finite Volume Discretization Strategymentioning

confidence: 99%

“…In all our test cases, the temporal discretization is based on the second-order Crank-Nicolson scheme (Ferziger and Perić, 1996), with a blending factor of 0.5 (0 meaning a first-order Euler scheme, 1 a second-order, bounded implicit scheme) and an adaptive time stepping based on the maximum initial residual of the previous time step (Kay et al, 2010), and on a threshold that depends on the Courant number (Co < 0.2). All advection terms of the model are treated implicitly to enforce stability.…”

Section: Finite Volume Discretization Strategymentioning

confidence: 99%

“…New SGS models are implemented. Concerning point 5, it is worth remarking that, according to Ferry et al (2003), the first-order term τ j in Eq. (15) must be limited to avoid the divergence of preferential concentration in a turbulent flow field (and to keep the effective Stokes number below 0.2).…”

Section: Solution Proceduresmentioning

confidence: 99%

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ASHEE-1.0: a compressible, equilibrium–Eulerian model for volcanic ash plumes

2016

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Abstract.A new fluid-dynamic model is developed to numerically simulate the non-equilibrium dynamics of polydisperse gas-particle mixtures forming volcanic plumes. Starting from the three-dimensional N-phase Eulerian transport equations for a mixture of gases and solid dispersed particles, we adopt an asymptotic expansion strategy to derive a compressible version of the first-order non-equilibrium model, valid for low-concentration regimes (particle volume fraction less than 10 −3 ) and particle Stokes number (St -i.e., the ratio between relaxation time and flow characteristic time) not exceeding about 0.2. The new model, which is called ASHEE (ASH Equilibrium Eulerian), is significantly faster than the N-phase Eulerian model while retaining the capability to describe gas-particle non-equilibrium effects. Direct Numerical Simulation accurately reproduces the dynamics of isotropic, compressible turbulence in subsonic regimes. For gas-particle mixtures, it describes the main features of density fluctuations and the preferential concentration and clustering of particles by turbulence, thus verifying the model reliability and suitability for the numerical simulation of highReynolds number and high-temperature regimes in the presence of a dispersed phase. On the other hand, Large-Eddy Numerical Simulations of forced plumes are able to reproduce the averaged and instantaneous flow properties. In particular, the self-similar Gaussian radial profile and the development of large-scale coherent structures are reproduced, including the rate of turbulent mixing and entrainment of atmospheric air. Application to the Large-Eddy Simulation of the injection of the eruptive mixture in a stratified atmosphere describes some of the important features of turbulent volcanic plumes, including air entrainment, buoyancy reversal and maximum plume height. For very fine particles (St → 0, when non-equilibrium effects are negligible) the model reduces to the so-called dusty-gas model. However, coarse particles partially decouple from the gas phase within eddies (thus modifying the turbulent structure) and preferentially concentrate at the eddy periphery, eventually being lost from the plume margins due to the concurrent effect of gravity. By these mechanisms, gas-particle non-equilibrium processes are able to influence the large-scale behavior of volcanic plumes.

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Section: Kinematic Decouplingmentioning

confidence: 99%

Section: Kinematic Decouplingmentioning

confidence: 99%

Section: Finite Volume Discretization Strategymentioning

confidence: 99%

Section: Finite Volume Discretization Strategymentioning

confidence: 99%

Section: Solution Proceduresmentioning

confidence: 99%

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ASHEE-1.0: a compressible, equilibrium–Eulerian model for volcanic ash plumes

2016

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On the transport modes of fine sediment in the wave boundary layer due to resuspension/deposition: A turbulence‐resolving numerical investigation

Cheng

Hsu

et al. 2015

JGR Oceans

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Previous field observations revealed that the wave boundary layer is one of the main conduits delivering fine sediments from the nearshore to continental shelves. Recently, a series of turbulenceresolving simulations further demonstrated the existence of a range of flow regimes due to different degrees of sediment-induced density stratification controlled by the sediment availability. In this study, we investigate the scenario in which sediment availability is governed by the resuspension/deposition from/to the bed. Specifically, we focus on how the critical shear stress of erosion and the settling velocity can determine the modes of transport. Simulations reveal that at a given wave intensity, which is associated with more energetic muddy shelves and a settling velocity of about 0.5 mm/s, three transport modes, ranging from the well-mixed transport (mode I), two-layer like transport with the formation of lutocline (mode II), and laminarized transport (mode III) are obtained as the critical shear stress of erosion reduces. Moreover, reductions in the settling velocity also yield similar transitions of transport modes. We also demonstrate that the onset of laminarization can be well explained by the reduction of wave-averaged bottom stress to about 0.39 Pa due to attenuated turbulence by sediments. A 2-D parametric map is proposed to characterize the transition from one transport mode to another as a function of the critical shear stress and the settling velocity at a fixed wave intensity.

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Stochastic Lagrangian Simulation of Particle Deposition in Turbulent Channel Flows

Sikovsky

2015

Flow Turbulence Combust

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A locally implicit improvement of the equilibrium Eulerian method

Cited by 50 publications

References 17 publications

ASHEE-1.0: a compressible, equilibrium–Eulerian model for volcanic ash plumes

ASHEE-1.0: a compressible, equilibrium–Eulerian model for volcanic ash plumes

On the transport modes of fine sediment in the wave boundary layer due to resuspension/deposition: A turbulence‐resolving numerical investigation

Stochastic Lagrangian Simulation of Particle Deposition in Turbulent Channel Flows

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